text:
The era of all things connected: Smart house crowned in the era [...]
The era of all things connected: Smart home crowned
In the digital and Internet era, concepts such as the Internet of Things (IoT) are becoming prevalent and powerful in the real world. Along with the development and perfection of artificial intelligence, Internet-connected devices are getting cheaper and easier to access. Smart home also becomes practical, handy, useful and brings many good experiences, help users more.
Smart home becomes the inevitable technology trend of the future.
he application and integration of modern technologies and smart home systems make life more efficient, easier to control, economical, productive, integrated and sustainable. All electrical and electronic devices are automated to replace people performing some management and control operations … Compared to normal houses, all operations must be done manually according to the form of turn on/off, adjust big/small …. Then smart home helps homeowners can control devices only by voice or a few light touches on smartphones.
Vietnam does not out of technology, in the real estate sector, many developers have quickly grasped and utilized technology in their projects to create a huge competitive advantage. One of the names pioneering high-tech applications and deploying smart houses into Vietnamese real estate projects is Sunshine Group. In the context, technology is still considered luxurious, by investing more technology in the project will cost more for investors, Sunshine Group has invested in a methodical way to deploy and develop Smart utilities through technology subsidiary – Sunshine Tech.
Thanks to the achievements of technology, smart houses make people’s lives more comfortable, modern and class.
Sunshine Group’s Smart home impresses at Vietnam Mobile Day 2019
Speaking at Vietnam Mobile Day 2019 – the event is considered the biggest annual festival in the whole technology industry, which brings together the leading experts in this field, Mr. Pham Minh Tuan – Sunshine Tech Branch Manager, Ho Chi Minh City of Sunshine Group said: “Today, the development of the Internet, especially wifi wireless network has become popular not only in offices and offices but also in each family, creating premise for the birth of SmartHome and Smart Living ecosystem. At Sunshine Group’s SmartHome apartments, the technology enables homeowners to enjoy comfortable living with simple operations on phones and tablets, and easily interact with every home appliance wherever you are”.
Sunshine Tech’s booth at Vietnam Mobile Day 2019 event introducing products using advanced and modern technologies is being applied to Sunshine Group’s apartments.
Sunshine Tech Smart Living’s highlight is the integrated control of all devices into a mobile application, making it easy to monitor the status and create scripts to control the device according to user’s wish. For example: When going home, press the “Go home” button, the system will automatically turn on the corridor lights, open 50% blinds, turn on the air conditioner and heater … Users can enjoy the comfort and convenience that Sunshine Tech’s Smarthome ecosystem brings, improves the quality of life.
Mr. Pham Minh Tuan – Director of Sunshine Tech Branch, Ho Chi Minh City presented IoT, Smarthome and Mesh Wifi network at the big event that attracted more than 9,000 attendees.
SmartHome system will help synchronize and control all electrical equipment. Besides easy control, the system also provides analysis, statistics on electricity, water usage, equipment uptime, etc. From there, it helps users have an overview of the usage of device in their house. High safety and security, identity verification through many censorship steps, helps users feel secure when using the system. In addition to remote control via Smartphone, the system also integrates control of voice devices through linking with smart speakers like Alexa, Google Assistant, …
In addition, Sunshine Tech is also developing its own smart speaker to integrate into its own system with the function of supporting listening, calling, device control, etc. Users can interact with Smart Speaker in Vietnamese, for example: “OK Sunshine: Turn on the air-conditioner in the living room”, “OK Sunshine: How’s the weather today?”, … The smart speaker will respond to all user requests, helping bring convenience and comfort when use.
Sunshine Tech’s booth attracted a lot of attention from attendees.
Contributing to Vietnam Mobile Day 2019 just took place on June 14 in Hanoi, Sunshine Tech also introduced the most impressive breakthrough technology products to apply to smart apartments such as smart switch, IR Gateway central controller, data meter reading device, water meter, motion detection system, intelligent parking system …
Sunshine Tech’s booth attracted a lot of visitors to the event. Mr. Nguyen Minh Chien (35 years old, Cau Giay) – a customer attending the event said: “I was really surprised by the optimal technology applications in the apartments at Sunshine. Certainly, living in such a comfortable and modern home, residents will feel extremely wonderful.”
Through this event, Sunshine Tech wanted to emphasize serious investment, self-development and mastering of smart devices. At the same time, Sunshine Tech also wants to share its knowledge with the developer community in Vietnam to develop together, compete equally with imported products.
A few notable images of Sunshine Tech during the Vietnam Mobile Day 2019 event:
Presentation by Sunshine Tech representative, Mr. Pham Minh Tuan – Director of Ho Chi Minh City branch caused great attention to attendees.
Vietnam Mobile Day 2019 event gathers many experts and people who are interested in technology.
The customer is particularly impressed with the technology products introduced by Sunshine Tech at the event.
The organizer awarded certificates to representatives of Sunshine Tech.


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I am here at home on the Oregon Coast and it's business as usual for me! One of the inspiring parts of being an artist is creating outside of my studio and outside of my normal routine. I love being on the road and challenging myself to find new ways to create and while I am here I have all kinds of inspiration to share!
This driftwood city project has been in my brain for the last 6 months (it is actually what inspired my recycled cardboard city!)- the only problem is there is not much driftwood at my home in Southern California so I knew as soon as I was back at home in Oregon I would be creating a little city out of driftwood!
If you have been to the Oregon Coast you will know that there is a CRAZY amount of driftwood- like piles and piles and piles of old wood weathered by the sand and the sea. I spent my childhood crawling around these piles looking for little treasures and to this day it is still one of my favorite ways to spend time!
I collected a bag full of interesting shaped driftwood.
I began to put pieces together, stack and plan out little houses and buildings.
I glued all of the pieces together (with craft glue) to form little buildings that could stand on their own.
Then I began to paint my city in my makeshift studio- the backyard!
This little guy snuck up and startled me while I was painting but hung out and watched me for a while! (yep, this is Oregon!)
I added simple details with permanent pen.
I gathered up my city and my production assistant (my mom) and went to the beach to photograph.
The best part of this project (as is with all of my city projects) is taking the pictures in a unique environment! My mom and I had a blast setting up the city in the along the waters edge.

domain: geography


text:
Sieve the flour, sugar, baking powder and salt into a large bowl.
Beat the buttermilk, butter and egg together in a separate bowl then pour onto the dry ingredients now beat the mixture together until it forms a smooth batter. Now gently stir in the blueberries.
Heat a large frying pan over a medium heat then once the pan is hot using a pastry brush oil the bottom of the frying pan using the sunflower oil.
Drop as much of the batter as you like into the frying pan and spread around into a circle. Fry until you see bubbles forming on the surface then using a spatula flip the pan cakes over and fry for about 1-2 minutes now remove from the pan making sure both sides are golden broth and serve. Repeat this frying stage until you have used up all the batter.
Ingredients140g Plain flour
2 tbsp Caster sugar
2 tbsp Baking powder
½ tsp salt
3 tbsp Melted butter
1 Large egg
5 oz Sunflower oil for greasing the pan

domain: food


text:
What should one make of the Leninfall story? Was the demolition of the Lenin monuments just an unfortunate episode, a passing spasm of symbolic violence fueled by social upheaval and resulting in the loss of part of the country’s cultural heritage (some of the monuments, such as the one removed in Kyiv, had unquestionable artistic value)? Or did it reflect a broader change in society and its perception of itself and its past? And if the latter is more true than the former, then what does that memory shift tell us about the direction taken by Ukrainian politics and society since the time of the EuroMaidan and the Revolution of Dignity?
None of these questions can be adequately addressed without taking into account the spatial dimension of the Leninfall. Taking place in the midst of Ukraine’s most profound political crisis since the demise of the Soviet Union, the Leninfall was as much the outcome of political strife as were the wars of historical memory. Politics and memory had been closely interlinked in Ukraine at least since the Orange Revolution of 2004, and both have had very strong regional components. Regionalism in Ukrainian politics and memory had been strengthened by the Revolution of Dignity and the loss of the Crimea and parts of eastern Ukraine to Russia-led separatist projects, which also mixed politics and memory, as evidenced by the “Novorossiia” project, rooted in the imperial past, and the creation of the Donetsk and Luhansk people’s republics, inspired by the Soviet experience and endowed with the Soviet legacy.
The exploration of the regional dimensions of Ukrainian historical identity and the politics of memory based on that regionalism is the main objective of the “History and Identity” module of the MAPA: Digital Atlas of Ukraine Project developed by the Ukrainian Research Institute, Harvard University. This module is the result of collaboration with two main partners: the project titled “Region, Nation, and Beyond: An Interdisciplinary and Transcultural Reconsideration of Ukraine” under the leadership of Professor Ulrich Schmidt at the University of St. Gallen, Switzerland, and a project undertaken by the Razumkov Center in Kyiv under the title “The Formation of the Common Identity of Ukrainian Citizens in New Circumstances: Peculiarities, Prospects and Challenges.” Some information for the module was provided by the Institute of National Memory of Ukraine.
The maps developed by MAPA Project Manager Kostyantyn Bondarenko and MAPA Research Fellow Viktoriya Sereda are based on a spatial analysis of the data produced by two surveys conducted in Ukraine in March 2013 and March 2015 by the University of St. Gallen Project with the support of the Swiss National Foundation and the Wolodymyr George Danyliw Foundation, as well as a December 2015 survey conducted by the Razumkov Center and funded by the Swedish International Development Cooperation Agency, the Konrad Adenauer Foundation, and the Ministry of Foreign Affairs of the Netherlands under the auspices of the “Social Transformation in Ukraine and Moldova” project. The first two surveys included 6,000 respondents aged 18 and above, while the third covered more than 10,000 respondents of the same age category.
The discussion that follows is based on the data and maps produced on the basis of the above-mentioned surveys. Both the maps and the databases, including the formulation of survey questions and responses to them, expressed as percentages of all responses, may be consulted on the module page of the MAPA website. The MAPA maps reproduced below represent one or more layers of the spatial information available on the website. Although the MAPA-produced maps and layers of information provide the basis for this discussion, it also draws on maps and data produced by other mapmakers and projects acknowledged in the footnotes.
While this paper focuses mainly on the Leninfall and seeks primarily to offer preliminary answers to the questions formulated at the start of this section, it is also designed as a demonstration of the possibilities inherent in GIS-based mapping and spatial analysis based on it and is presented as an invitation to further research into the spatial dimensions of Ukrainian memory politics and Ukrainian society at large.


Technology & Combat Characteristics
The transformable mobile suit MSZ-006 Zeta Gundam developed by the Anti-Earth Union Group (AEUG) is originally considered far too complex and expensive for mass production. But Karaba, the organization that serves as the AEUG's terrestrial forces, takes note of the Zeta Gundam's effectiveness and redesigns it to create the mass production type MSK-006 Zeta Plus (later redesignated as the MSZ-006A1). Because this machine is intended exclusively for use in the atmosphere, its space flight systems and atmospheric entry features are eliminated. However, its cost-performance ratio and flight capabilities are superior to those of the prototype Zeta Gundam.
Instead of the flying armor used by the original Zeta Gundam, the Zeta Plus is equipped with variable geometry wing binders similar to those of the MSN-00100 Hyaku Shiki. These wing binders improve the flight characteristics of the wave rider form, giving it a cruising range of hundreds of kilometers, and in mobile suit form they can be used for AMBAC maneuvering rather than simply becoming dead weight. The Zeta Plus is also equipped with two beam cannons in the side armor, which are connected directly to its movable frame so that energy supply and fire control can be performed without using the mobile suit's hands.
- 60mm Vulcan Gun
- Two 60mm Vulcan Gun mounted on the sides of Zeta Plus' head. Having low power but a high rate of fire, they are mainly used to ward off advancing enemies, intercept missiles, etc. Comparing with Zeta Gundam, Zeta Plus' extended head allows it to carry 80% more ammunition for its vulcan guns.
- Thigh Beam Cannon
- A pair of beam cannons are mounted on the thighs of the Ζeta Plus A1, and are usable in both mobile suit and waverider modes. They are power rated at 2.4 MW.
- Beam Saber
- Beam sabers are standard equipment on all Federation MS. The beam sabers use Minovsky particles held in place by an I-Field to form an effective cutting surface that can slice through nearly any material. The Zeta Plus A1 has a pair of beam sabers stored within the top of the thigh beam cannons.
- A custom shield used by the Zeta Plus A1, it not only protects the mobile suit from physical and beam attacks, but also serve as the nose unit in waverider mode.
- Beam Rifle
- A custom, handheld, ranged beam weapon used by Zeta Plus A1, it has the same level of firepower as the original Zeta Gundam's. It is powered by a replaceable e-pac and usable in both mobile suit and waverider modes.
- Beam Rifle~ReZEL's version
- A beam rifle used by the Zeta Plus A1 in U.C. 0096. It is first used by the RGZ-95 ReZEL and besides functioning as a ranged weapon, it can also emit a beam blade from its muzzle, allowing it to act as a long beam saber.
The Z Plus, although designed at first only for a semi-official series Gundam Sentinel, got its designs to retcon the supposedly earlier model, the MSZ-006 Zeta Gundam. After the Gryps Conflict ended, the Earth Federation wanted the design of the Ζeta Gundam to be reworked, so that it was more streamlined, less complex, and, most importantly, cheaper to manufacture, but so that it would still retain all of the major strengths of the original unit. The Ζ-Plus line of mobile suits was the answer to the Federation's requests.
The first Zeta Plus rolls out in November of U.C. 0087, and the new machine is assigned to Karaba units such as the 18th Tactical Fighter Aggressor Squadron (18TFAS) based aboard the Garuda class carrier Audhumla. Karaba eventually deploys about twenty machines, three of which are painted in white and orange test colors for demonstration purposes. Rumor has it that one of these colorful machines is used by the legendary ace pilot Amuro Ray in his role as commander of 18TFAS. Some of the Zeta Plus A1 remain in service even in U.C. 0096 and are stationed at some Earth Federation ground bases.
Notes and Trivia
- The Zeta Gundam's name is derived from "Zeta", which is the sixth letter of the Greek Alphabet - which may be reference to its model number.
- Gundam Sentinel Special Edition, Model Graphix, ISBN 4-499-20530-1
- MSZ-006A1 Zeta Plus A1 on MAHQ.net
- MSZ-006A1 Zeta Plus A1 on Gundams Over Germany
- MSZ-006A1 Zeta Plus A1 on GearsOnline.net


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Jan 14 to Jun 10
Saturdays 2pm to 3:15pm
Northeastern Illinois University's Campus Recreation department offers recreational activities & swim lessons for the whole family! Our pool has an 8 lane 25 yard lap area and a 14 foot diving well with 1-meter and 3-meter diving boards. Programming includes open swim, adult and children learn-to-swim lessons, water polo club, underwater hockey, Women's Only Hour, and much more.

domain: hobby


text:
If you are thinking about starting a family or have conceived, you may have heard of the AMH test. The AMH test measures the levels of the anti-Müllerian hormone in your blood. A blood test can determine AMH levels, and it’s a good idea to get tested for AMH levels if you’re about to start a family. Read ahead to find out more about this test, why you should get it done, and how much the AMH test costs.
What is AMH?
AMH stands for anti-mullerian hormone. This hormone is produced by small follicles in your ovaries and is a good indicator of your ovarian reserve. In other words, it can tell us how many eggs you have left and how likely you are to conceive.
What To Expect From An AMH Test?
There are several reasons why you should get tested for AMH levels. If you are over 35 or have a family history of early menopause, your doctor may recommend the test. It can also be helpful if you have had difficulty conceiving in the past. Getting the AMH test is simple and quick, and the AMH test cost is very reasonable. Your doctor will interpret the results of your AMH test and give you advice on whether or not you should try to conceive now, or not.
Here’s how an AMH test usually goes:
· First, your doctor will draw blood from a vein in your arm.
· The results of the test will be back within a few days.
· Your doctor will use the test results to estimate your ovarian reserve.
· This information can help them understand how likely it is that you’ll be able to conceive and help them plan fertility treatments if necessary.
Who Should Get Tested for AMH?
· If you are a woman of reproductive age, it is recommended that you get tested for AMH levels. It is because AMH levels can give your doctor important information about your fertility.
· If you have been trying to conceive for six months or longer without success, you should get tested for AMH levels. It is because low AMH levels may be a sign of infertility.
· If you are over the age of 35, it is also recommended that you get tested for AMH levels. It is because AMH levels decline with age, and this decline can be an early warning sign of menopause.
· Finally, if you have any medical conditions that could affect your fertility, such as endometriosis or PCOS, it is recommended that you get tested for AMH levels. It is because low AMH levels may be a sign of these conditions.
The Benefits of Testing for AMH
· First, it can help you understand your fertility. If your AMH levels are low, it may mean that you have a lower chance of conceiving. However, it’s important to remember that it is just one factor in fertility. Many other factors contribute to fertility, so even if your AMH levels are low, you may still be able to conceive.
· Second, testing for AMH can help you plan for your future. If you know your AMH levels are low, you may want to consider freezing your eggs or pursuing other fertility treatments. This way, you can give yourself the best chance of having a baby when you are ready.
· Third, testing for AMH can help you understand your risk of certain diseases. Women with higher AMH levels have a lower risk of developing ovarian cancer. So, if your test results show that your AMH levels are high, it could signify that you have a lower risk of ovarian cancer.
· Fourth, testing for AMH can help you make decisions about contraception. If you’re using contraception and your goal is to prevent pregnancy, knowing your AMH level can help you choose the best method. For example, if your AMH levels are low and you’re using the pill, you may want to consider switching to a different method of contraception.
How to Interpret Your Results?
A blood sample is drawn for the AMH test. The results of the test will indicate how much AMH is in your blood. The higher the number, the more AMH you have. There is no “normal” range for AMH levels, so your doctor will interpret your results based on your age and fertility goals. A higher AMH level is generally better if you’re younger than 35 and trying to conceive. A lower AMH level may be normal for you if you’re over 35 or experiencing fertility issues.
Generally speaking, higher AMH levels indicate better ovarian reserve. It means that you have a higher chance of conceiving. Conversely, lower AMH levels may indicate a lower chance of conceiving.
It’s important to note that AMH levels can fluctuate over time. Your doctor may recommend repeated testing if you’re trying to conceive and have trouble doing so. It won’t burden your wallet as an AMH test cost is not too much. Your doctor may also use your AMH results to predict your response to fertility treatments like in vitro fertilization (IVF). A higher AMH level means you’re likely to respond well to treatment and have a successful pregnancy.
If you have any questions about your results or what they mean for your fertility, ask your doctor. They can help you understand the next steps you should take to reach your family-building goals.
The Bottom Line
AMH stands for anti-müllerian hormone, a protein produced by the cells surrounding your eggs in the ovaries. AMH levels can give your doctor important information about your reproductive health, including how many eggs you have left and whether you’re likely to respond well to fertility treatments. If you’re over 35 or have any other risk factors for infertility, your doctor may recommend AMH testing. The test is quick and easy, and the AMH test cost is also very reasonable. It can give you valuable information about your fertility.
To know more about keep reading morning chart.

domain: medical


text:
The AHVLA’s latest update on reported incidences of the Schmallenberg virus (SBV) in Great Britain claims “no change” since the previous report released by the agency on July 9, 2012.
The AHVLA‘s latest update on reported incidences of the Schmallenberg virus (SBV) in Great Britain claims “no change” since the previous report released by the agency on July 9, 2012.
The report, released today (July 16, 2012), shows:
- 53 cases on cattle premises,
- 219 on sheep holdings,
- 3 cases in both cattle & sheep on same premises.
The most recent area to be confirmed with the disease was Oxfordshire, which saw its first farm reporting infection in cattle as of the report July 9, 2012.
The Oxfordshire report is also the last recorded new case of the disease in the UK.
The current figures, as released on July 16, are:
|County||Positive holdings (Sheep)||Positive holdings (Cattle)||Positive holdings (cattle and sheep)||Total|
|Cornwall and Isles of Scilly||2||1||0||3|
|East Riding and Norht Lincolnshire||0||1||0||1|
|Isle of Wight||2||1||0||3|
|Leicestershire and Rutland||1||0||0||1|
|North Somerset and Gloucestershire||4||0||0||4|
|Somerset excluding North Somerset||3||0||0||3|
Background information and an information note for farmers and vets (in both English and Welsh) are available to view and/or download from the VLA website Schmallenberg virus page.
- AHVLA has adjusted some of the current total numbers for the counties where some premises lie close to a county boundary.
This has no bearing on the distribution of infection when it occurred last summer or on the Government’s assessment of the risk of incursion of potentially infected midges from continental Europe. It is a consequence of more detailed ongoing work following up affected premises in order to assess impact.
SBV image © AHVLA

domain: biology


Dre spills the tea on a lot of Pop culture news! What's going on in our world? Let's learn from it, pray about it and some of it we can enjoy! Feedback? Email email@example.com Also check out some Youtube channels with new, fresh, gospel music and more! #PopCulture #Tea #WendyWilliams #VenusWilliams #SerenaWilliams #LilNasx #Faith #Talk #Entertainment--- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/irene-washington/message
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text:
Welcome – A Nice Idea Every Day
Image makers Vivien Weyrauch and Fabian Roettger believe in an out-of-the-box approach, always finding inventive ways to tell visual stories. Based between LA and Berlin, they originally trained as cinematographers and have since developed their own unique approach to directing, working with a wide array of analog and digital techniques in music videos, fashion films and commercials.
They have worked with bands like The Knife, Palma Violets and Peter, Bjorn & John and directed commercials for brands such as Sony, Adidas, i-D, Nike and River Island. They were nominated as Best New Director at the UK Music Video Awards, and featured as one of the New Video Visionaries by Dazed. They have shown their work in exhibitions and festivals worldwide.
Click the image to see their work.

domain: entertainment


text: “For the divine nature may be communicated or imparted in some sense; and indeed while it is essentially and necessarily singular, it is certainly plural in its personal manifestations. Hence we have the Father, Son, and Holy Spirit equally divine, though personally distinct from each other. We have in fact, but one God, one Lord, one Holy Spirit; yet these are equally possessed of one and of the same divine nature. Some conceive of God as mathematical unit; and as a thing cannot be both mathematically singular and plural, one and three, at the same time and in the same sense, they deny the true and proper divinity of the Son of God and of the Spirit of God. But it would seem to us, that they reason not in harmony with the sacred style of inspiration. But why should we imagine that there cannot be a plurality of personal manifestations in the divine nature any more than in the angelic or human, especially as man was created in the image of God?” — Alexander Campbell, The Christian System, p. 8.

domain: literature


text:
Sterling Silver Personalized Round Keychain
Add a stylish and personal touch to your keys! Your choice of a personalized engraving is presented in chic block letters on this polished sterling silver disc keychain. Makes a lovely gift for yourself or someone else. Select the engraving option you would like from the dropdown menu below. Sterling silver keychain. Please note that personalized items cannot be returned.
Due to the incredible value on your Clearance selection, no additional discounts apply.
Product Details (for Monogram Sterling Silver Round Keychain)
1 1/4 inches
1 1/8 inches
All weights and measures are approximate.
Ross-Simons Presentation Box Your purchase includes an elegant Ross-Simons presentation box.
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domain: design


text:
Morrisons is “moving in the wrong direction” and “making a big mistake” after authorising the use of GM feed by its poultry farmers for the first time in a bid to alleviate soaring input costs, according to the anti-GM lobby.
Morrisons said it would allow poultry farmers supplying both meat and eggs to use GM feed, after the cost of non-GM feed increased by 25% in the past two years [Defra].
“This policy will be increasingly difficult and costly to maintain as the availability of non-GM protein (soy) decreases,” said a spokesman.
And the NFU welcomed Morrisons’ move. “There is no doubt this will help poultry producers meet social and environmental commitments while producing safe, affordable protein,” said chief poultry adviser Kelly Watson.
But Soil Association policy director Peter Melchett said Morrisons was risking its reputation with consumers. “They’re moving in the wrong direction from a reputational point of view. Sooner or later customers will tell Morrisons they want to buy their poultry elsewhere.
“It also goes against the grain in the rest of Europe,” Melchett added.
And GM Freeze campaign director Pete Riley said Morrisons was “making a big mistake”, citing a Which? survey - presented at the Oxford Farming Conference - that found 70% of consumers felt it was important for retailers to have policies barring GM ingredients in animal feed.
Supermarkets introduced a unilateral ban on poultry feed in 2001 following a consumer backlash against GM crops - while continuing to allow GM feed for other livestock. The u-turn by Morrisons, following a similar decision by Asda in September 2010, suggests that supermarkets are starting to test consumer attitudes to GM in the wake of soaring inflation.
Research by the British Science Association, published earlier this month, indicated that 25% of Britons are not concerned by GM foods, compared with 17% in 2003.
Tesco told The Grocer all its fresh and frozen poultry as well as own-brand organic meat would continue to be fed non-GM feed. And Sainsbury’s confirmed its chicken, turkey and duck were all non-GM fed.
However, Sainsbury’s added it was aware of the increasing pressure on the availability of non-GM food crops. “We continue to keep the situation under regular review to ensure continuity of supply.”

domain: economics


On Sale Now! Save 2% on the Sealed Power 4095M10 Main Bearing Set by Sealed Power at Split Racing. MPN: 4095M10. Hurry! Limited time offer. Offer valid only while supplies last. Copper-lead alloy. Popular for fatigue resistance strength. Provides conformability required for older apps. This standard material is comparable to competitors performance bearing. Note this material offers less resistance to wear corrosion than other materials..Comes with full brand warranty. Fits multiple makes and models (contact seller with your vehicle for fitment compatibility information).
Product Description & Reviews
Copper-lead alloy. Popular for fatigue resistance strength. Provides conformability required for older apps. This standard material is comparable to competitors performance bearing. Note this material offers less resistance to wear corrosion than other materials..
Features & Highlights
- Comes with full brand warranty
- Fits multiple makes and models (contact seller with your vehicle for fitment compatibility information)
Rod & Main Bearings
51 x 27 x 75 inches
3.88 x 2.13 x 6.19 inches
Have questions about this item (4095M10), or would like to inquire about a custom or bulk order?
If you have any questions about this product by Sealed Power, contact us by completing and submitting the form below. If you are looking for a specif part number, please include it with your message.
mpn: 8-7195CH, ean: 0099998019514,
Sealed Power produces application-engineered internal replacement components, including pistons, piston rings, engine bearings, camshafts, oil pumps, timing components and valvetrain products.Connecting Rod Bearing - Speed Pro - Standard - Small Bloc...
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Material: TM-77Standard Shaft Diameter: 1.9981/1.9985Vertical Oil Clearance: 0.0017/0.0032Maximum Wall: 0.0801Bearing O.D. or Housing Bore: 2.1605/2.1610Max Length: 0.7400Material: TM-77. Standard Shaft Diameter: 1.9981/1.9985. Vertical Oil Clearance...
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Sealed Power 5707 BCA BEARING. FITS 7.5,7 5/8, CHEV 8.5 AND CHEV 8.2 AND CHEV 12 BOLTWheel Bearing. 2.252 in OD. 1.402 in ID. 0.698 in Width. Steel.


text:
Building dinnerware sets is a wonderful̴adventure and Modigliani wants you to enjoy it for years to come. With that in mind, we add new products and collections that can mix with our current lines allowing you to easily reinvent your table as we go! We like to think outside the box and suggest combinations that will surprise and delight! Of course, the potential combinations are almost endless so we will continue to add new ideas as the inspiration strikes us. If you love our chosen combination, you can order it exactly as it is! If you want to change it up, have at it. Who knows, maybe we will add your creation to the Mix and Match Collection!
Discover the Inspiration for Jingle Mix and Match̴
Put a jingle in your step with our POP Circle Collection which can be translated into a modern ornament design during the holidays and when mixed with the rich red of our Rosso Collection and deep green of our charger, it becomes even more festive. Add some Via Veneto red flatware and Tivoli green glassware to round out the table.
- Set of four pieces
- Handmade in Italy
- Dishwasher Safe
Dinnerware Set Includes

domain: artistic


This weekend’s music thread, h/t to Fuzzy Dunlop for the suggestion, is dedicated to Dr. Christine Blasey Ford, the women who confronted Jeff Flake in the elevator and all the very brave women who have been courageously standing up for the dignity and rights of women against hostile, misogynist men in positions of power
This is a moment and these are Americans that will be remembered in history as making a meaningful difference in the course of this nation.
So this weekend’s music thread is dedicated both to women and their noble traits on display right now, when they’re most needed and most challenged. Bravery, intelligence, strength and determination.
Share your favorite songs about women and their heroism.
We’re all in this together, men and women but women are stepping up with unique bravery and defiance as leaders in this Trump era of oppression.
Share your theme songs for this women-led revolution and as a tribute to the women who put their fears last and their fight for justice first.
A tribute to the courage of all women and of all men who stand tall for women’s rights.
Excellent choice A! How are ya?
Hi, FD – Thank you and doing good, apologize for the delay. We are starting next week on getting our basement finished after more than twenty years. So keeping busy clearing out the stuff there from more than twenty years ago. 😉 There is a lot of accumulated we-can-put-it-there-until-later, and now later has arrived! – Great to see you, take care. 🙂


Toshiba announced All-in-One PC
Toshiba just unveil the DX1215 All-in-One PC powered by Intel's 2nd Gen i-Core processors, full 1080p HD display and built-in Onkyo speakers powered by powered by Waves MaxxAudio processors.
The DX1215 will also feature Generation Intel® Core™ i5 or Core i7 processor, USB 3.0 and 2.0, HDMI ports, 1TB 7200 RPM hard drive and a pre-paired Bluetooth wireless keyboard and wireless mouse. The Toshiba DX1215 will be available exclusively at Bestbuy on July 2, 2011 just in time for the fireworks and will cost $929.99.
Check the press photo and full PR after the break.


text:
Coastal storms and other hazards threaten the New York region and could necessitate the evacuation of individuals living in designated evacuation zones, as well as patients or residents in health care facilities in the same zones. While most jurisdictions have robust sheltering plans that include Special Medical Needs Shelters (SMNS), these facilities generally provide only basic medical care, such as oxygen administration, wound care, and the monitoring of vital signs.
Because of this limitation, health care facilities outside evacuation zones or in higher evacuation zones (i.e., New York City’s Evacuation Zones 5 and 6) are advised to have surge plans to accommodate medically vulnerable community members living in evacuation zones and hospital patients who were evacuated from other facilities. Since medically vulnerable community members could be brought to a hospital before or after the storm, hospital surge plans should account for receiving individuals in both timeframes. While predicting the acuity level of medically vulnerable community members is difficult, based on previous experiences, many of them will require skilled nursing level care.
This document is designed to help health care facilities—specifically hospitals—modify their existing surge plans for the purposes of accommodating medically vulnerable community members. Five sections follow:
- Activation, Integration, and Scalability of the Surge Plan for Medically Vulnerable Community Members
- Surge Space
- Equipment and Supplies
Each topic area includes points for consideration when developing and/or modifying a facility’s plans, and specific examples adapted from actual facility plans.


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|Número de publicación||US6606612 B1|
|Tipo de publicación||Concesión|
|Número de solicitud||US 09/374,491|
|Fecha de publicación||12 Ago 2003|
|Fecha de presentación||13 Ago 1999|
|Fecha de prioridad||13 Ago 1998|
|Número de publicación||09374491, 374491, US 6606612 B1, US 6606612B1, US-B1-6606612, US6606612 B1, US6606612B1|
|Inventores||Man Mohan Rai, Nateri K. Madavan|
|Cesionario original||The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration|
|Exportar cita||BiBTeX, EndNote, RefMan|
|Citas de patentes (3), Otras citas (25), Citada por (25), Clasificaciones (5), Eventos legales (9)|
|Enlaces externos: USPTO, Cesión de USPTO, Espacenet|
This application claims the benefit of U.S. Provisional Application Nos. 60/096,660, filed Aug. 13, 1998, entitled “Aerodynamic Design Using Neural Networks,” and 60/113,310, filed Dec. 22, 1998, entitled “Neural Network-Based Redesign of Transonic Turbines for Improved Unsteady Aerodynamic Performance,” both of which are herein incorporated by reference.
The invention described herein was made by employees of the United States Government and may be manufactured and used by or for the Government for governmental purposes without the payment of any royalties thereon or therefor.
1. Technical Field
The present invention is directed toward an improved method and system for design optimization using composite response surfaces. These composite response surfaces are constructed by combining neural networks with other interpolation/estimation techniques such as polynomial fits. In particular, the present invention relates to a flexible process for the efficient use of simulation and experimental data in aerodynamic design optimization.
2. Description of the Related Art
Considerable advances have been made in the past two decades in developing advanced techniques for the numerical simulation of fluid flows over aerodynamic configurations. These techniques have now reached a level of maturity where they can be used routinely, in conjunction with experiments, in aerodynamic design. However, aerodynamic design optimization procedures that make efficient use of these advanced techniques are still in their infancy.
The design of aerodynamic components of aircraft, such as wings or engines, involves a process of obtaining the most optimal component shape that can deliver the desired level of -component performance, subject to various constraints, e.g., total weight or cost, that the component must satisfy. Aerodynamic design can thus be formulated as an optimization problem that involves the minimization of an objective function subject to constraints. A variety of formal optimization methods have been developed in the past and applied to aerodynamic design. These include inverse design methods, adjoint methods, sensitivity derivative-based methods, and traditional response surface methodology (RSM).
Inverse design methods, as the name suggests, are strictly used for inverse design (for example, to design a wing that produces a prescribed pressure distribution). The known inverse design methods do not take into account the viscosity of the fluid and are therefore used in preliminary design only. This method is applicable to a small class of aerodynamic design problems, such as those where the entire pressure distribution can be specified a priori.
Adjoint methods provide the designer with the gradient of the objective function that is being minimized in order to obtain the optimal design. Starting from an initial component shape that is reasonable, the design space is searched using this gradient information. The main advantage of this method is that the gradient information is obtained very rapidly. However, the method has several shortcomings. It is difficult to use this method to arrive at an optimal design when several engineering disciplines (such as, aerodynamics, structures, and heat transfer) need to be considered simultaneously. It requires a completely different formulation for every discipline and for every set of governing equations within each discipline. It is also difficult to rapidly evaluate design tradeoffs which require that the constraints be changed many times. It is also not possible to use existing design or experimental data, or partial or unstructured sets of data, to influence the design process.
Sensitivity derivative-based methods typically require that many aerodynamic solutions be obtained in order to compute the gradient of the objective function. As the number of design parameters increases, these methods can become computationally expensive to use. They are also sensitive to any noise in the design data sets. Additionally, like the adjoint methods, it is not always possible to use existing design or experimental data, or partial or unstructured sets of data, to influence the design process. Design tradeoff studies require that additional aerodynamic simulations be performed, thus incurring additional expense. However, they are applicable to a wide range of aerodynamic design problems.
Response surface methodology (RSM) represents a framework for obtaining optimal designs using statistical methods such as regression analysis and design of experiments. Traditional RSM, as it has been used in practice, employs low-order regression polynomials to model the variation of the aerodynamic quantities, or some measure of optimality, with respect to the design variables. This polynomial model of the objective function in design space is then searched to obtain the optimal design. Several such polynomial models may have to be constructed to traverse the region of design space that lies between the initial design and the optimal design. This method does not suffer from the shortcomings of the methods mentioned above. However, modeling complex functional behaviors using RSM will necessitate the use of high-order polynomials with their attendant problems.
Artificial neural networks have been widely used in aeronautical engineering. Recent aerodynamic applications include, for example, flow control, estimation of aerodynamic coefficients, compact functional representations of aerodynamic data for rapid interpolation, grid generation, and aerodynamic design. Neural networks have been used to both model unsteady flows and to optimize aerodynamic performance parameters. Significant cost savings have been realized in reducing wind tunnel test times by using neural nets to interpolate between measurements. Neural network applications in aeronautics are not limited to aerodynamics and may be applied in structural analysis and design as well as many other technical disciplines.
In order for neural networks to be used effectively in design, it is imperative that the design space be populated both adequately and efficiently with simulation or experimental data. A sparse population results in an inaccurate representation of the objective function in design space while an inefficient use of aerodynamic data in populating the design space could result in excessive simulation costs. Current applications of neural networks are restricted to simple designs involving only a few design parameters because a linear increase in the number of design parameters often results in a geometric increase in the number of datasets required to adequately represent the design space.
Therefore, a need exists for adequately and efficiently populating large-dimensional design spaces to achieve an optimal design. More particularly, to be able to use existing design or experimental data, or partial or unstructured sets of data, to influence the design process. The subject invention herein, solves these problems in a novel manner not previously known in the art.
It is therefore the object of the present invention to provide an improved method and system for design optimization, using composite response surfaces, and having the following characteristics:
ability to start from a generic design that is far from optimal;
easy and economical to use in large dimensional design space;
ability to handle a variety of design objectives;
ability to easily impose constraints, incorporate design guidelines and rules of thumb;
ability to handle both simulation and experimental data simultaneously;
ability to handle partial data sets and data that lack structure;
insensitivity to noise in the data;
ability to handle data of varying fidelity as the design evolves;
ability to handle unsteady data (unsteady effects) in the design process;
flexibility to handle additional data as it becomes available;
ability to rapidly perform design trade-off studies;
ability to leverage the multi-tiered parallelism possible on modern
distributed and parallel computers; and
ability to execute designs that are influenced by multiple disciplines (multi-disciplinary optimization).
The foregoing object is achieved, as is now described, using a method and system that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks. The present invention employs a unique strategy called parameter-based partitioning of the given design space. In the design procedure, a sequence of composite response surfaces based on both neural networks and polynomial fits are used to traverse the design space to identify an optimal solution. The composite response surface has both the power of neural networks and the economy of low-order polynomials (in terms of the number of simulations needed and the network training requirements). The present invention handles design problems with many more parameters than would be possible using neural networks alone and permits a designer to rapidly perform a variety of trade-off studies before arriving at the final design.
The above as well as additional objects, features, and advantages of the present invention will become apparent in the following detailed written description.
The novel features believed characteristic of the invention are set forth in the appended claims. The invention itself however, as well as a preferred mode of use, further objects and advantages thereof, will best be understood by reference to the following detailed description of an illustrative embodiment when read in conjunction with the accompanying drawings, wherein:
FIG. 1 is a graphical representation of a parabolic function and the neural network approximations of this function;
FIG. 2 depicts a geometrical diagram of a three-layer neural network for use with the method of the present invention;
FIG. 3 depicts geometrical shapes for two- and three-dimensional simplexes also for use with the method of the present invention;
FIG. 4 shows a flowchart of a design process for optimizing a design using both neural networks and polynomial fits to construct a composite response surface in accordance with one preferred embodiment of the present invention;
FIG. 5 is a graphical presentation showing the progression of design optimization for an airfoil in accordance with one preferred embodiment of the present invention;
FIG. 6 shows a graph comparing the instantaneous pressure contours in the reference and optimized designs of a gas generator turbine; and
FIG. 7 shows a graph comparing the instantaneous pressure contours in the reference and optimized designs of a transonic turbine.
With references now to the drawings wherein like reference numerals refer to like and corresponding parts throughout. While there are several methods that can be used to represent the functional behavior of design data, neural networks are particularly suitable for multidimensional interpolation where the data is not structured. Since most design problems in aerodynamics involve a multitude of parameters and datasets that often lack structure, neural nets provide a level of flexibility not attainable with other methods. In fact, partial datasets or even a single data point intermingled with more complete datasets can be used to influence the design process.
Aerodynamic design data has traditionally been obtained from a variety of sources. In the past, experiments and simple analyses have provided the majority of data used in design. More recently, the methods of Computational Fluid Dynamics (CFD) have been used to generate a significant portion of the design data. A hierarchy of approximations for the governing partial differential equations (i.e., the Navier-Stokes equations), ranging from the simple potential flow equations to the Euler and Reynolds-averaged, Navier-Stokes equations, have been used for this purpose. Typically, the simpler and lower fidelity potential flow solutions have been used in the initial stages of design because they are relatively inexpensive to compute; and because a large number of solutions are required at this stage. Here the term fidelity is used to denote the extent to which the system of equations faithfully represents the physical characteristics of the flow. The higher fidelity Euler and Navier-Stokes solutions are generally used in the final stages of design because of the high cost of computing these solutions. It has been found that neural networks provide a natural framework within which a succession of solutions of increasing fidelity can be represented and subsequently utilized for optimization and design thus reducing overall design costs. The design data can come from a variety of sources, including experiments and computations. Rules-of-thumb that designers have evolved over a number of years can also be incorporated within the optimization routines as constraints. These facts are of considerable importance to the aircraft industry which has accumulated enormous amounts of experimental data and numerous design rules over a number of decades.
As mentioned earlier, in order for neural networks to be used effectively in design, it is imperative that the design space be populated both adequately and efficiently with simulation or experimental data. One aspect of the invention disclosed here, namely the idea of parameter-based partitioning of the design space, directly addresses this problem. In parameter-based partitioning, the functional dependence of the variables of interest with respect to some of the design parameters is represented using neural networks, and the functional dependence with respect to the remaining parameters is represented using other interpolation/estimation techniques, e.g., polynomial regression methods. This approach is an extension of traditional response surface methods that are based on polynomials alone. The use of neural networks in conjunction with other methods results in a composite response surface that models the functional behavior in design space. When first or second-order polynomials are used, the number of data sets required increases in a linear or quadratic manner, respectively, with the number of parameters.
Parameter-based partitioning greatly reduces the number of data sets required to populate the design space and thus enables designs involving a larger number of parameters than would be possible using neural networks alone. Consider a simple design that involves three design parameters. Typically, 33 or 27 simulations would be required to populate this three-dimensional design space. Clearly, this process results in inordinately large number of simulations in high-dimensional design spaces. For example, the number of simulations that would be required for a 100-parameter design problem is 3100, or about 5×1047. On the other hand, for a linear representation within a simplex, the current approach would require between 100-200 simulations.
In addition to drastically reducing the computational requirements to obtain the simulation data, the method of the present invention also has a dramatic impact on the neural net training process. First, the reduction in the total amount of simulation data greatly reduces the training requirements. Second, the use of multiple neural networks to represent the data also contributes to reduced training times. This is because a part of the complexity of representing the function is transferred from the neural network to the polynomial approximation.
A second aspect of the present invention relates to the choice of the initial design point. Clearly, the further the optimal design is from this initial design point the larger the region of design space that needs to be represented by the composite response surface. An inordinately large number of data may then be required to adequately populate the design space. The method of the present invention uses a sequence of composite response surfaces that constitutes a search process. Thus, the number of simulations required are relatively modest.
Therefore, in accordance with the present invention, composite response surfaces are constructed using a combination of neural networks and other interpolation/estimation techniques (low order polynomials, Fourier transforms, etc.) By way of example and not of limitation, the composite response surfaces will be constructed using neural networks and polynomials (as the interpolation/estimation technique). It should be appreciated that the primary motivation for constructing a composite response surface based on neural networks and polynomials comes from a careful examination of the relative strengths of these two approaches in interpolating design data. Neural networks provide a very general framework for estimation in multiple dimensions. Referring now to FIG. 1 there is shown a graphical representation 40 of a parabola 42 given by:
and the neural network approximations to this function. Referring once again to FIG. 1, the network is shown trained with three training pairs (Curve A) and with five training pairs (Curve B) 46. The generalization ability obtained when only three training pairs 44 are used is inadequate. It should be noted that the training error in this case (Curve A) was decreased by 25 orders of magnitude. A marked improvement in generalization is seen with the use of five training pairs 46.
The graphs 40 of FIG. 1 demonstrate that neural-network based generalization can become unreliable when the amount of available training data is very small. However, the use of a single linear neuron with a preprocessor that provides the input nodes with the bias and the values of x and x2, would yield a perfect fit with just three training pairs. It should be noted that such a single linear neuron is, in essence, a polynomial fit. The advantage of the polynomial fit provided by the single linear neuron is that it requires a prescribed minimum number of data points for a given number of polynomial terms, and, this number increases in a polynomial fashion with the number of dimensions. For example, if a quadratic fit was used to represent the data, the number of data points required to compute the coefficients of the polynomial would increase quadratically with the number of dimensions. If the target function can be locally approximated using low-order polynomials then there is an advantage to using polynomial fits instead of neural networks.
From the example and discussion above, the present invention combines conventional polynomial approximations on s-dimensional simplexes with the flexibility that neural nets provide. This results in a mathematical model whose complexity can be adjusted on a dimensional basis to suit the function being modeled, thus reducing the amount of data required. However, it should be noted that this assumes that the local variation of the design objective function with some of the geometric parameters can be accurately represented using low-order polynomials. The terminology s-dimensional simplex used above refers to a spatial configuration of s dimensions determined by s+1 equi-spaced vertices, on a hyper-sphere of unit radius, in a space of dimension equal to s. By this definition, a two-dimensional simplex is an equilateral triangle that is circumscribed by a unit circle. The method of modeling functional behavior using polynomials whose coefficients are estimated from data defined on simplexes is referred to as a Koshal design.
By way of example, but not of limitation, consider a design scenario where the data can be generated for prescribed values of the design parameters. Additionally, assume that the variation of the aerodynamic data of interest with respect to some of the design parameters is not very complex (this may be because the parameter variations are small or because the underlying function is simple), and, hence, does not require the generality of a neural network-based estimation scheme. Therefore, simple polynomials can be used to represent the variation of the function with these parameters and a neural network can be used for the remaining parameters.
Referring to FIG. 2 there is shown a three-layer neural network 50 (with two hidden layers 52 and 60). The variation of aerodynamic data along the surface of the airfoil is typically far more complicated than the variation with small changes in geometric parameter values. Hence, the neural network 50 is used to represent aerodynamic data variation in physical space. The first node 54 in the input layer is a bias node (input of 1.0). The second set of nodes are used to specify the physical location 56. In this particular two-dimensional design environment, the physical location 56 is specified by a single parameter, i.e., the axial location on the airfoil surface. Given t geometric parameters that determine the shape of the airfoil, assume that the variation of the first c parameters results in “complex” variations in the aerodynamic data and the variation of the remaining s parameters results in fairly “simple” variations in the data that can be represented by low-order polynomials (t=s+c). The third set of nodes 58 in FIG. 2 accept the first c geometric parameters. Pressure values corresponding to axial locations and geometry parameters specified at the input nodes are obtained at the output node 62.
The variation of the aerodynamic data with the remaining s variables is approximated using simple polynomials. For a linear variation, the points at which the data are determined are located at the vertices of a s-dimensional simplex and are at unit distance from the origin. In this case there are s+1 vertices and s+1 unknown coefficients to be determined. For a quadratic variation, in addition to the vertices of the simplex, the midpoints of all the edges are included as well. This results in (s+1)(s+2)/2 nodes and as many unknown polynomial coefficients that must be determined. FIG. 3 shows the points at which these data are required in two dimensions 64 (s=2) and three dimensions 66 (s=3) for a quadratic fit.
In the two-dimensional 64 case shown in FIG. 3 the pressure can be approximated as:
Given the pressure values p1,p2, . . . p6 at the vertices 68 of the simplex, the coefficients a1,a2, . . . a6 can be obtained from the following system of equations:
The generalization to higher-dimensional simplexes and higher-order polynomials is developed as described above wherein a certain minimum number of pressure values is required depending on the number of dimensions and the order of the polynomial used. However, the number of pressure values that are typically used is more than this minimum (greater than six in the example above). This helps reduce the effect of noise in the data on the accuracy with which the response surface models the functional relationship between the aerodynamic variable (e.g. pressure) and the geometric parameters. The coefficients in this case are estimated using a least squares approach.
The method of combining neural networks and traditional polynomial fitting techniques of an embodiment of practicing the present invention is as follows:
First, obtain simulation data at each of the vertices of the simplex used for the polynomial fit. Multiple simulations will be required at each vertex if some of the geometric parameters are represented by the neural net; and
Second, assign one neural net for every vertex of the simplex. Train each neural net with the simulation data generated for the corresponding vertex. The input for each net includes the bias value, the axial location along the airfoil and the “complex” geometric parameters.
The pressure corresponding to a given axial location and a set of geometric parameter values are obtained through the following two-step process:
First, obtain the pressure at each of the vertices of the simplex using the corresponding neural nets. This is easily done since the axial location on the airfoil and the values assigned to the “complex” geometric parameters are known; and
Second, compute the estimates of the polynomial coefficients and then use the prescribed values of the “simple” geometric parameters to obtain the estimate for the required pressure value.
The trained networks together with the polynomial fit constitute the composite response surface. The accuracy with which this composite response surface represents the actual functional dependence of the aerodynamic quantities on the design parameters is determined by the accuracy of the original aerodynamic data, the number of simulations used to populate the design space, the network parameters such as the number of neurons in the hidden layers 52 and 60 of FIG. 2, and the order of the polynomial used. The accuracy with which the networks represent the training data is given by the training error, TE, that is minimized to obtain the network weights. For any one of the neural networks, this training error is given by:
where Pi n is the set of target pressures, Pi n is the output pressure from the network, imax is the total number of data points on the surface of the airfoil at which the target pressures are prescribed, and nmax is the number of simulations used to train this particular network. Note that nmax has to be large enough that the functional dependence of the pressure on the “complex” variables is modeled accurately by the neural networks. The number of neurons is increased successively until the training error is sufficiently small.
The accuracy with which the composite response surface represents the pressure as a function of the physical and geometric parameters can be estimated by comparing the pressure distributions of the computed validation datasets (which are different from the training set) to the pressure distributions obtained using the composite response surface for these validation cases.
This validation process is essential in establishing the adequacy of the generalization capabilities of the response surface. Typically, this is carried out at the centroid of the simplex.
Referring now to FIG. 4, there is shown the steps for implementing the method of the present invention. The objective function in step 90 is obtained from the design requirements. In step 100 the initial geometry or design point is specified. Ideally, this initial geometry should be as close as possible to the optimum. In aerodynamic design, there are several approaches, e.g., inverse design procedures, meanline analyses, and streamline curvature-based methods, that can be used to obtain this initial geometry. This geometry serves as the centroid of the first simplex.
Next, as shown in step 120, the design space is populated in the vicinity of the initial geometry by constructing a simplex in design space around this centroid and the geometry corresponding to each of the vertices (for a linear variation) and interior nodes (for quadratic or higher-degree polynomials) is obtained in step 140. The process then generates grids for each geometry in step 160. At this stage in the process, step 180, the fidelity level is chosen and solutions are generated for each geometry. Next, in steps 200 and 220 the neural networks are trained and the polynomial coefficients that define the pressure variation within the simplex are computed. The input nodes of the neural nets will typically contain parameters that correspond to the physical location on the aerodynamic component and those geometric parameters that give rise to “complex” behavior of the objective function. At this point, step 240, the composite response surface is defined.
Referring once again to FIG. 4, the process continues to step 260 for a search of the region of the design space represented by the composite response surface. Various methods can be used to accomplish this constrained search. Geometrical and other constraints and rules-of-thumb that designers have evolved can be incorporated within this search procedure (for example, using a penalty function method). In addition, constraints that limit the search procedure to the volume of the simplex are also incorporated in the search. In step 280, it is determined whether the local optimum obtained in the previous step lies on or outside the boundaries of the simplex. If the design conditions have not been met in step 300 of FIG. 4, i.e., the search procedure culminates at a point on or outside the boundaries of the simplex, then this point is chosen as a new centroid in step 320 and the process is repeated until the search culminates inside the simplex. However, the process can be stopped at any time when the design is deemed adequate as shown in step 340.
Additionally, several types of design refinements may be necessary. A particular design may require many iterations before the optimal solution is obtained. One reason for this could be that the initial design is very different from the target. The need to minimize overall design costs dictates that one obtain a preliminary design based on low-fidelity, low-cost simulations (e.g., potential flow solutions). The process of FIG. 4 is then repeated using higher fidelity simulations (e.g., Euler or Navier-Stokes solutions). A second level of refinement may involve repeating the process of FIG. 4 with a simplex of reduced size. Finally, the geometry corresponding to the optimal design is used to verify that it performs as required by the design specifications.
The optimal design obtained above is a point in design space that meets all the initial design criteria. However, after obtaining this optimal design, the designer often wishes to modify the target or the constraints to arrive at a better and improved design, or analyze a variety of what-if scenarios. Several hundred such trade-off studies may be required before the final design is defined. These analyses can be performed very efficiently by representing the functional dependence of the aerodynamic quantities in the vicinity of the design obtained in the process steps of FIG. 4 using the composite response surface approximation and once again searching this space with the new targets and constraints embedded in the search procedure. Clearly, this process can only be used if the new targets are contained in the region of design space where the generalization capabilities of the response surface are adequate. It has been shown with aerodynamic design that the search procedure requires two to three orders of magnitude less computing time than that required for simulation and training the network. This allows the designer to rapidly perform a variety of trade-off studies that would naturally involve changing the constraints to resolve design conflicts or improve the design.
Aerodynamic design efforts typically deal with steady flows. However, there are many instances where unsteady effects can have a significant impact on the overall performance of the component. The current design methodology provides a natural framework for including unsteady effects in the design process. This is possible because of the very general manner in which the objective function can be defined.
As an illustration, this invention can be used in a specific unsteady aerodynamic design problem, namely, transonic high pressure (HP) aircraft engine turbine design. The flow in HP turbines is complicated by the presence of shocks, wakes, tip leakage, and other secondary flow effects. These shocks, wakes, and vortical flows are ingested by downstream stages, resulting in complex interactions with one another and with the flow in these stages. All of these effects are complicated further by the inherent unsteadiness of the flow field that results from the relative motion of the rotor and stator rows and gives rise to unsteady interactions both within the HP turbine stages and between the HP turbine and the adjacent low pressure (LP) turbine stages. These unsteady effects result in poor aerodynamic performance, unsteady blade stresses, fatigue, vibration and reduced blade life.
The present design method can be used to improve the unsteady aerodynamic performance of transonic turbines by optimizing the shape of the stator and rotor airfoils. This is accomplished by formulating an objective function that minimizes the unsteady amplitudes on the stator vane (or rotor blade) subject to the constraint that the tangential force on the rotor airfoil (i.e., turbine work output) does not decrease. The pressure amplitude is used as a measure of the unsteadiness in the flow field and is defined as the range of temporal pressure variation on the airfoil surface.
In the case of turbines where unsteady shocks are present, the design process can be used to weaken, or eliminate, the shocks. The presence of unsteady shocks results in large unsteady pressure amplitudes. Thus the pressure amplitudes are directly related to the shock strength. Hence a reduction in the unsteady amplitudes on the airfoils can have the additional benefit of weakening or eliminating the shocks in the flow field. This example also illustrates the use of high-fidelity simulations, such as unsteady Navier-Stokes computations, to include all the relevant physics of the problem and to steer the optimization within the framework of the present invention.
The following applications have been chosen to demonstrate how some of the objectives of the invention have been met.
The present invention was used to reconstruct the shape of a turbine airfoil given the desired pressure distribution and some relevant flow and geometry parameters. The shape of the airfoil was not known a priori. Instead, it was evolved from a simple curved section of nearly uniform thickness. The evolved optimal airfoil closely matched the shape of the original airfoil that was used to obtain the pressure distribution. This constitutes a “blind” test. FIG. 5 illustrates the evolution of the design. The evolution of the shape of the airfoil is shown on the left, while the corresponding pressure distributions compared to the target pressure distribution are shown on the right. Clearly, the surface pressures approach the target pressure as the design progresses. The optimal airfoil shown at the bottom has a pressure distribution that is very close to the target pressure distribution.
In this application, the following attributes of the design optimization method were demonstrated:
1. Ability to start from a generic design that is far from optimal;
2. Easy and economical to use in large-dimensional design space;
3. Ability to handle a variety of design objectives;
4. Ability to handle data of varying fidelity as the design evolves;
5. Flexibility to handle additional data as it becomes available; and
6. Ability to leverage the multi-tiered parallelism possible on modern distributed and parallel computers.
The first example deals with the application of this method to the redesign of a gas generator turbine with the goal of improving its unsteady aerodynamic performance. The turbine is a two-stage configuration with an aggressive design characterized by high turning angles and high specific work per stage. Although the turbine was designed to operate in the high-subsonic regime, an unsteady analysis showed very strong interaction effects including an unsteady moving shock in the axial gap region between the stator and rotor rows. It is hypothesized that the strength of this shock can be reduced by optimizing the airfoil geometries, and the overall unsteady aerodynamic performance of the turbine can thereby be improved. Since the shock can only be discerned by an unsteady aerodynamic analysis, a time-accurate Navier-Stokes solver is coupled to the neural net-based optimizer and provides simulation inputs to it. FIG. 6 compares the instantaneous pressures in the reference and optimized designs of a gas generator turbine. Clearly, the shocks, labeled A and B on FIG. 6, present in the reference design (which appear as clustered contours in the region between the stator and rotor rows) have been eliminated in the optimized design. The present invention yields a modified design that is close to the reference design and achieves the same work output, yet has better unsteady aerodynamic performance since the flow through it is shock-free.
The second example deals with the application of the invention to the redesign of a transonic turbine stage. The design goal is to improve its unsteady aerodynamic performance by weakening the shocks in the stage and thus reducing their effect on turbine aerodynamics. The tangential force on the rotor is constrained so that it does not decrease during the optimization process.
The application of this design method yielded a new design with a slightly different geometry. FIG. 7 compares the instantaneous pressure contours in the reference and optimized designs of a transonic HP turbine and shows that the unsteady stator trailing edge shock in the reference design has been weakened in the optimized design. This leads to lower unsteady pressure amplitudes on the airfoil surfaces and improved aerodynamic performance. These reductions in unsteady pressure amplitudes were obtained without changing the tangential force on the stator and rotor airfoils or the work output of the turbine. The uncooled stage efficiency for the optimized design was nearly identical to that for the reference design.
Therefore, in accordance with the present invention, the following attributes of the design optimization method were demonstrated:
1. Ability to handle a variety of design objectives;
2. Ability to easily impose constraints, incorporate design guidelines and rules of thumb;
3. Insensitivity to noise in the data;
4. Ability to include time-varying data (unsteady effects) in the design process;
5. Ability to rapidly perform design tradeoff studies; and
6. Ability to leverage the multi-tiered parallelism possible on modern distributed and parallel computers.
It is also important to note that although the present invention has been described in the context of providing a composite response surface to optimize a design, those skilled in the art will appreciate that the mechanisms of the present invention are capable of being distributed as a program product in a variety of forms to any type of information handling system, and that the present invention applies equally regardless of the particular type of signal bearing media utilized to actually carry out the distribution. Examples of signal bearing media include, without limitation, recordable type media such as floppy disk or CD ROMs and transmission type media such as analog or digital communications links.
The above description of the method of obtaining the composite response surface for a specific design problem is only an example of how this invention can be applied and should not be construed as the only application of the invention. The invention is capable of other and different embodiments, and its several details are capable of modifications in various obvious respects, all without departing from the invention.
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text:
In a remarkable tale that defied political boundaries, Gershon Baskin, a Jewish man based in New York City, had forged an unlikely friendship with Hamas leader Ghazi Hamad over a clandestine 17-year communication. They had both courageously aimed to pave the way for peace between Israel and Palestine. However, their world was shattered on October 7 when an act of violence tore through their delicate bond.
Baskin and Hamad had defied norms and stereotypes, engaging in behind-the-scenes conversations to promote understanding and harmony in the pursuit of resolving the longstanding conflict. Their enduring friendship had become an oasis of hope amid the chaos, their words transcending borders and ideologies.
This unique relationship between Baskin and Hamad had spanned nearly two decades. Their perseverance and mutual respect had allowed them to navigate the treacherous landscape of mistrust, hostility, and bloodshed. They had become confidants, sharing their deepest aspirations and frustrations, as they sought ways to bring an end to the Israeli-Palestinian dichotomy that had haunted generations.
However, their connection was severed when Hamad publicly endorsed the tragic events of October 7, leaving Baskin devastated and disillusioned. The friendship that had withstood the test of time crumbled under the weight of conflicting ideas and irreconcilable actions.
In the aftermath of the heartbreaking rupture, unanswered questions echo through the minds of many. What prompted Hamad’s sudden divergence from the olive branch of peace? Was this a testament to the fragility of peace efforts in the region? Could their years of secret communication have achieved a different outcome if not for this tragic turn of events?
Q: What is Hamas?
A: Hamas is a Palestinian political and military organization that emerged in 1987, with its primary goal being the establishment of an independent Palestinian state.
Q: Who is Gershon Baskin?
A: Gershon Baskin is a Jewish individual hailing from New York City. He devoted years to fostering communication and understanding between Israelis and Palestinians, aiming for a peaceful resolution to the ongoing conflict.
This remarkable story serves as a reminder of the complexities surrounding the Israeli-Palestinian conflict, where even the most unlikely alliances can emerge in the pursuit of peace. While this particular bond has fractured, the underlying message of dialogue and understanding remains ever relevant. As the world watches and waits for a breakthrough, we must not forget the efforts of individuals like Baskin and Hamad, who dared to believe that peace was within reach, even if only for a fleeting moment.

domain: politics