Daily Archives: June 24, 2021

(ABC4) Luckily for local residents, the shocking collapse of a condominium building in the Miami area on Thursday morning is extremely rare, and a similar event has virtually no chance of occurring in Utah, according to one of the states top structural engineers.

Matthew Roblez, who heads up the structural engineering team at McNeil Engineering in Sandy and was named the 2016-17 Engineer of the Year by the American Society of Civil Engineers, tells ABC4 he was shocked by the news out of Florida due to the singularity of the event. Roblez says these kinds of collapses are virtually non-existent in the United States.

It could be any number of things, and thats what the investigation will be. So, it could be a design error, it could be a construction error, and it could have been, I hate to say it, but it could have been some form of sabotage, because quite frankly, what makes this so odd is were not a third world country and this just doesnt normally happen. Its just not a regular occurrence, Roblez explains.

At this point, what could have caused the 12-story building collapse in Surfside, Florida is up for speculation. The collapse reportedly occurred at around 1:30 a.m. on Thursday morning, and due to a high capacity of residents, many of the 130 affected unit inhabitants are feared dead. At least one death has been confirmed and search and rescue teams have already pulled 35 survivors from the rubble.

While some work was being performed on the roof the building, officials have all but ruled that out as a possible cause for the destruction.

Roblez guesses what could have happened was a long-term deterioration that was invisible to the naked eye and went unnoticed until the sudden disaster.

I cant think of anything else that would just cause all of that, he supposes. A lot of times in buildings, you might have a pipe leak that is just flowing and seeps into the concrete or something like that and destroys the real reinforcing. No ones going to know until theres an issue. A building is a lot like a car engine, you dont know theres something wrong until its really wrong.

He continues to explain that what typically happens is that a buildings maintenance staff should be walking around, making regular inspections. Should this person notice anything troublesome, a call is made to an engineer, like Roblez, who can come in, assess the situation, and make recommendations to correct any issues. Roblez explains he recently underwent this process on a downtown Salt Lake City parking structure that was built in the 1970s.

As for the building in Florida, which Roblez found was built in 1980, he is unsure of what could have happened. He wonders if perhaps the construction team, using technology and understanding that has since become outdated, did not foresee any issues that could occur as a result of building in Southern Floridas challenging climate conditions. Nowadays, and in Utah, when builders raise structures, they adjust the materials accordingly depending on what to expect as the seasons change.

When we do parking garages here in Salt Lake, we know theres going to be a lot of salt thrown down, so we take steps to put traffic coatings or admixtures in the concrete. Now maybe in 1980, in Miami, they may not have understood a lot of the climate issues, and so they just put regular concrete or something like that, he guesses.

While what is sure to be an upcoming investigation as to the cause should shed light on what happened on the other side of the country, Roblez is confident that a similar story of a sudden collapse in Utah is not a realistic possibility, even with earthquake concerns constantly looming. He says damage would likely clearly be shown before a building in Utah would come crashing down.

For something like this to happen is so extremely rare, I would say that there are zero worries for something like this to happen here.

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Could a building collapse happen here? One of Utahs top engineers explains - ABC 4

As a recent New York Times article highlighted, self-driving cars are taking longer to come to market than many experts initially predicted. Automated vehicles where riders can sit back, relax, and be delivered to their destinations without having to watch the road are continuously relegated to the not-too-distant future.

Theres not just debate on when this driverless future will arrive, theres also a lack of consensus on how well get there, that is, which technologies are most efficient, safe, and scalable to take us from human-driven to computer-driven (Tesla is the main outlier in this debate). The big players are lidar, cameras, ultrasonic sensors, and radar. Last week, one lidar maker showcased some new technology that it believes will tip the scales.

California-based Luminar has built a lidar it calls Iris. Iris not only has a longer range than existing systems, its also more compact; gone are the days of a big, bulky setup that all but takes over the car. Perhaps most importantly, the company is aiming to manufacture and sell Iris at a price point well below the industry standard.

Lidar scans a vehicles surroundings by sending out pulses of light in or near the visible spectrum, illuminating targets then analyzing the reflections that come back and using them to create high-resolution 3D maps. Advances in laser technology and computing speed over the last decade or so made lidar a more viable technology for widespread use.

Earlier iterations used spinning mirrors to direct the light beams, but that made for clunky systems with lots of moving parts. In 2016 Quanergy unveiled the first solid-state lidar, the S3, steered with a chip containing a million tiny antennas. With a range of 200 meters, the company planned to sell the S3 for $250 (at least three of these would be required to give the vehicle full visibility, putting the cost at $750).

Iris uses waves of light up to 1,550 nanometers long (905 nanometers is the standard). The longer length yields increased visibility, allowing the map to incorporate objects others might miss, whether because theyre small, dont reflect light well, or are too far away.

Luminar says Iris can detect and classify objects up to 250 meters away, or 500 meters for larger objects, and can detect the speed of moving objects in 3D (like a car changing lanes or a pedestrian stepping into the street). Rather than multiple lasers working in concert, Iris has just one laser and accompanying receiver, with two axis scanning mirrors giving the lidar a 120-degree by 30-degree field of vision.

Luminar CEO Austin Russell estimates Iris will initially be priced at around $1,000, and over time brought down to $500. Just two years ago, Wired reported industry leader Velodynes lidar costing about $75,000. Since then, though, Velodyne has also begun work on a solid-state lidar it aims to price below $500.

Luminar plans to integrate Iris into robotaxis and self-driving trucks through a design its calling Blade, a sleek gold-colored strip encircling the vehicle and containing all its sensors.

One of the most vocal detractors of lidar has been Elon Musk, who called the technology a fools errand and said anyone relying on it was doomed. A May sighting of a Tesla Model Y outfitted with Luminar lidar caused some speculation about whether Musk was reversing course, but as one analyst pointed out, its more likely that Tesla is using lidar to test and validate its own self-driving system, which relies primarily on cameras.

With or without Tesla as a customer, though, Luminar seems to be doing fine: the company made headlines last year when it secured a contract with Volvo, saying the Swedish automakers cars would reach Level 3 autonomy in 2022. As reported by The Verge, Luminar also has deals with Audi, Toyota Research Institute, Daimler, and Chinese automaker SAIC, among others.

A lot of the discussion around self-driving cars focuses on the supposed safety improvements the technology will herald. Humans, the story goes, are negligent and at times even reckless, the cause of over 33,000 accidents and 36,000 deaths per year in the US alone. But putting these huge-sounding numbers in context, you could actually argue that humans are very good at driving; theres about one death from motor vehicle crashes per 100 million miles traveled.

Nevertheless, no fatalities is better than some, and thats what Luminar wants (well, Luminar and anyone whos ever driven or ridden in a car). Russell told The Verge that the company is moving towards the vision of zero collisions, building the uncrashable car. It will be a while yet before we can determine whos the better driver, but incremental advances like Iris seem to indicate that computers are (slowly) catching up to us.

Image Credit: Luminar

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An 'Uncrashable' Car? Luminar Says Its Lidar Can Get There - Singularity Hub

The potential reductions in California are more dramatic, with a potential for 43% carbon savings. California's grid relies on renewable energy for nearly half of its electricity, much of it from low-carbon sources such as solar and wind, which contribute to significant variations in carbon intensity, a measure of carbon emissions per unit of energy consumed. As states increase their reliance on renewable energy sources, their variability will increase, too, offering similar opportunities to shift usage to times when carbon intensity is lowest.

Carbon reductions from automated EV charging could have a significant impact on reaching carbon emissions goals to slow climate change, and while EV charging is the most obvious case, similar opportunities for savings apply to other large loads in the home. The best opportunities for load shaping are activities that can be scheduled flexibly, like running a dishwasher or washing machine during overnight hours to have clean clothes and dishes ready when they're needed in the morning. For these cases, automation can provide the right balance of meeting consumer needs and optimizing cost, carbon emissions, and constraints of the grid.

The study examined consumers' EV charging patterns using over 100,000 sessions of in-field EV charging data and time-based carbon intensity data for 30 major regional grid balancing authorities for utilities. It found that charging dynamically to minimize carbon utilization was consistently more effective at reducing carbon than Time of Use rates.

The results show that smart home automation can dynamically adjust energy usage to address both grid constraints and carbon emissions goals. A separate study of 1100 California homes conducted by Sense found that 55% of electricity usage in the evening time frame could be shifted to other times during the day or reduced. Using an automated, dynamic approach, utilities can incentivize customers to reduce peak emissions by shifting their activities, including EV charging, similar to the current incentives to reduce peak demand.

Carbon reductions are influenced by the regional mix of energy sources, with some regions offering a potential for higher reductions because of greater variability of carbon intensity in their fuel sources. Among the top 10 balancing authorities, CAISO (California Independent System Operator) had the highest variation in carbon intensity at 307%, followed by SWPP (Southwest Power Pool) at 259%, ERCOT Electric Reliability Council of Texas) at 197% and BPAT (Bonneville Power Authority Transmission) at 181%. For more details, see the complete study.

The analysis showed that most regions can achieve significant carbon reductions by automating EV charging to take advantage of the cleanest energy sources as they come onto the grid. As more states and regions increase the share of energy produced by renewable sources, the carbon savings potential will increase across the country.

Said Sense CEO Mike Phillips, "This EV study is an example of what can be done as we add intelligence to home infrastructure. As we work on decarbonizing the grid, because of the increased use of intermittent low-carbon energy sources, it is becoming increasingly important to influence not only how much power is being used, but when it is used. Fortunately, there are many things in the home where people only care about the result - not when the energy is used. EV charging is a great example, but automation can extend to other key consumers of energy as we build intelligence into the infrastructure of the home."

Said Wenbo Shi, CEO and co-founder of Singularity Energy: "This study demonstrates the potential of data-driven carbon intelligence to improve energy management strategies and cost-effectively reduce carbon emissions. We are filling a gap between decarbonization targets measured in tons of carbon and existing energy management strategies that are still kWh and cost driven. There is a massive opportunity to apply the technology to EVs and other smart devices at scale to rapidly accelerate the transition towards a clean energy future."

Implications for Utilities' Demand Management Strategies With EV adoption predicted to grow rapidly, propelled in part by the Biden administration's plan to build out a national network of 500,000 EV charging stations, utilities are predicting big increases in electricity usage from EV charging over the coming decade. At the same, aggressive carbon reduction goals at the state and federal levels have mandated that utilities must reduce carbon emissions.

While meeting CO2 reduction goals and anticipating new energy loads from electric vehicles, utilities need to keep pace with more intermittent sources of power. The ability to jointly optimize for CO2, cost, and grid constraints can provide the best performance at a system level. Dynamic signals from the power grid combined with EV charging automation could be used to inform utilities' incentive programs, influence consumer behavior, modulate peak demand as EV adoption grows, and reduce carbon.

About the StudyThe study examined 100,000 sessions of in-field electric vehicle charging data and analyzed the location- and time-based fuel mix of the power grid to characterize the carbon intensity of common EV charging patterns. It drew on anonymized Sense home energy data and high-quality carbon intensity data from Singularity Energy's Carbonara platform. Previous analyses of carbon intensity have relied on annual averages that can be two or three years old. Combining these real-time data sets, the study simulated EV charging for carbon intensity to identify carbon reductions. For more details, get the complete study. To learn more about other studies from Sense, visit sense.com/utilities

About SenseSense's mission is to reduce global carbon emissions by making homes smart and efficient. We empower people to care for their homes and families while contributing to a cleaner, more resilient future. Founded in 2013 by pioneers in speech recognition, Sense uses machine learning technology to provide real-time insights on device behavior, even for those devices that are not "smart." Customers rely on Sense for a wide range of uses including monitoring their home appliances, determining whether they left appliances running and identifying how to reduce their energy costs. Sense has received investments from two of the world's largest energy technology companies, Schneider Electric and Landis + Gyr. Sense is headquartered in Cambridge, Mass. To make sense of your energy, visit sense.com.

About Singularity EnergySingularity Energy enables the future of decarbonization through actionable data and novel algorithms. Carbonara, a carbon intelligence platform built by Singularity Energy, provides high-quality, actionable grid carbon data and a suite of innovative products, developer APIs, and intelligent tools for companies to build data-driven decarbonization solutions. Use cases of Carbonara include planning, reporting, and optimization for decarbonization and electrification projects like EV fleets, battery storage, smart devices, and 24/7 clean energy. Singularity Energy is a winner of the Harvard Physical Science & Engineering Accelerator, the Greentown Labs Bold Idea Challenge in partnership with Schneider Electric, the National Science Foundation Small Business Innovation Research Grant, and a URBAN-X Cohort 09 company. To turn your electricity data into precise carbon emissions insights, visit: https://carbonara.energy/

Media contact: [emailprotected]

SOURCE Sense

http://www.sense.com

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New Study Finds that EV Charge Automation Could Reduce Carbon Impact by up to 14% in US and by 43% in California - PRNewswire

In addition to tracking the home's carbon usage in real time, the Sense app has a look-ahead view that forecasts the carbon intensity (CI), so users can plan high energy tasks, such as laundry, dishwashing or charging electric vehicles, for times when carbon emissions will be lowest, reducing their home's overall carbon footprint.

In the app, users can also see a breakdown of the fuel types that are powering the home right now. The energy sources on the utility grid vary widely from region to region, and regions change their fuel mix over the course of a day, creating variations in CI.

The new CI feature is included in the Sense app for the Sense Home Energy Monitor and Sense Solar.It's also included in all Sense-enabled products, such as the Square D edition of the Sense app for the Wiser Energy Home Power Monitor and the Square D Energy Center from Schneider Electric.

What is Carbon Intensity?Carbon intensity is simply the amount of carbon dioxide emitted to generate a specific unit of power. The average CI across the country's utility grid is approximately 1 lb/kWh, which is roughly equivalent to the CI for natural gas. Consumers can lower their overall climate change impact by being aware of CI and shifting energy use to the times when the grid uses more green power.

In most regions of the country, the carbon intensity of electricity generated by utility power plants varies throughout the day. At some times of day, such as when solar and wind are generating lots of power, carbon emissions are low. During other times, power may come from sources that emit more carbon, like coal or natural gas power plants, increasing the carbon intensity of the power on the grid.

In regions that rely primarily on a single, continuous power source, like hydro or natural gas, the carbon intensity varies only slightly, while in others with diverse power sources, the carbon intensity (CI) can rise and fall over the course of a day or week.

How Sense Reduces Carbon EmissionsThe variability in CI offers an opportunity for Sense users to actively reduce their own home's impact on carbon emissions. In the Sense app, users can see their average CI and can see the current CI of the power they are using, which is based on dynamic data from the utility grid's regional balancing authority. The Sense app also shows a projection of carbon peaks and valleys over the next 12 hours. By scheduling activities when the CI from the grid is lowest, Sense users can reduce their own home's CI score and impact carbon emissions.

To provide this new functionality, Sense has partnered with Singularity and has integrated with their Carbonara platform for both real-time and projected CI. Carbonara analyzes and provides carbon intensity data for 30 grid balancing authorities across the country.

The Sense app already has several features that help homeowners reduce their home's energy usage and carbon footprints, including:

How Energy Smart Homes Can Address Climate ChangeIn the future, smart homes will be able to take advantage of these carbon intensity fluctuations automatically by responding to real-time signals from the utility grid. Said Sense CEO Mike Phillips: "Since the Sense app now knows the carbon intensity of power from the grid, we can start to automate activities in the home to take place when carbon intensity is low. For instance, in the future, Sense users will be able to schedule their dishwasher or EV charger to run when the CI is lowest. Smart homes can know the preferences of the residents (for instance, that the EV needs to be charged and ready to drive by 7am) and will take into account CI, energy costs, and constraints of the grid to find the right times to use energy, resulting in carbon and cost reductions and contributing to a more reliable power grid. This becomes increasingly important as we electrify our homes and cars, and as the grid uses more and more renewables."

"Homes are on track to become the single-largest consumer of electricity and homeowners realize that many of the resources currently being consumed to produce that electricity are negatively impacting our environment," said Michael Mahan, Vice President, Home & Distribution North America, Schneider Electric. "Now greater energy intelligence is being built into homes, including smart electrical panels, providing information and tools that allow homeowners to modify their behavior, empowering them to impact change for the betterment of the environment and their electricity bill."

About SenseSense's mission is to reduce global carbon emissions by making homes smart and efficient. We empower people to care for their homes and families while contributing to a cleaner, more resilient future. Founded in 2013 by pioneers in speech recognition, Sense uses machine learning technology to provide real-time insights on device behavior, even for those devices that are not "smart." Customers rely on Sense for a wide range of uses including monitoring their home appliances, determining whether they left appliances running and identifying how to reduce their energy costs. Sense has received investments from two of the world's largest energy technology companies, Schneider Electric and Landis + Gyr. Sense is headquartered in Cambridge, Mass. To make sense of your energy, visit: https://sense.com.

About Singularity EnergySingularity Energy enables the future of decarbonization through actionable data and novel algorithms. Carbonara, a carbon intelligence platform built by Singularity Energy, provides high-quality, actionable grid carbon data and a suite of innovative products, developer APIs, and intelligent tools for companies to build data-driven decarbonization solutions. Use cases of Carbonara include planning, reporting, and optimization for decarbonization and electrification projects like EV fleets, battery storage, smart devices, and 24/7 clean energy. Singularity Energy is a winner of the Harvard Physical Science & Engineering Accelerator, the Greentown Labs Bold Idea Challenge in partnership with Schneider Electric, the National Science Foundation Small Business Innovation Research Grant, and a URBAN-X Cohort 09 company. To turn your electricity data into precise carbon emissions insights, visit: https://carbonara.energy/

Press contacts:[emailprotected][emailprotected]

SOURCE Sense

http://www.sense.com

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Sense Debuts Carbon Intensity Tracking in the Sense App - PRNewswire

What happened at the beginning of the universe, in the very first moments? The truth is, we dont really know because it takes huge amounts of energy and precision to recreate and understand the cosmos on such short timescales in the lab. But scientists at the Large Hadron Collider (LHC) at CERN in Switzerland arent giving up.

Now our LHCb experiment has measured one of the smallest difference in mass between two particles ever, which will allow us to discover much more about our enigmatic cosmic origins.

The Standard Model of particle physics describes the fundamental particles which make up the universe, and the forces that act between them. The elementary particles include quarks, of which there are six: up, down, strange, charm, top, and bottom. Similarly, there are six leptons which include the electron, a heavier cousin called the muon, and the still heavier tau, each of which has an associated neutrino. There are also antimatter partners of all quarks and leptons which are identical particles apart from an opposite charge.

The Standard Model is experimentally verified to an incredible degree of accuracy but has some significant shortcomings. 13.8 billion years ago, the universe was created in the Big Bang. The theory suggests this event should have produced equal amounts of matter and antimatter. Yet today, the universe is almost entirely made up of matter. And thats lucky, because antimatter and matter annihilate in a flash of energy when they meet.

One of the biggest open questions in physics today is: why is there more matter than antimatter. Were there processes at play in the early universe that favored matter over antimatter? To get closer to the answer, we have studied a process where matter transforms into antimatter and vice versa.

Quarks are bound together to form particles called baryons (including the protons and neutrons that make up the atomic nucleus) or mesons, which consist of quark-antiquark pairs. Mesons with zero electric charge continually undergo a phenomenon called mixing by which they spontaneously change into their antimatter particle, and vice versa. In this process, the quark turns into an anti-quark and the anti-quark turns into a quark.

It can do this because of quantum mechanics, which governs the universe on the tiniest of scales. According to this counter-intuitive theory, particles can be in many different states at the same time, essentially being a mix of many different particles, a feature called superposition. It is only when you measure its state that it picks one of them. A type of meson called D0, for example, which contains charm quarks, is in a superposition of two normal matter particles called D1 and D2. The rate at which the D0 meson turns into its anti-particle and back again, an oscillation, depends on the difference in masses of D1 and D2.

It is difficult to measure mixing in D0 mesons, but it was done for the first time in 2007. However, until now, nobody has reliably measured the mass difference between D1 and D2 that determines how quickly the D0 oscillates into its antiparticle.

Our latest discovery, announced at the Charm conference, changes this. We measured a parameter that corresponds to a mass difference of 6.410-6 electron Volts (a measure of energy) or 10-38 grams, one of the smallest mass differences between two particles ever measured.

We then calculated that the oscillation between the D0 and its antimatter partner takes around 630 picoseconds (1 ps = 1 millionth millionth of a second). This may seem fast, but the D0 meson doesnt live long; it isnt stable in the lab and falls apart (decays) into other particles after only 0.4 picoseconds. So it will typically disappear long before this oscillation occurs, posing a serious experimental challenge.

The key is precision. We know from theory that these oscillations follow the path of a a familiar type of wave (sinusoidal). Measuring the start of the wave very precisely, we can infer its full period as we know its shape. The measurement therefore had to reach record precision on several fronts. This is made possible by the unprecedented amount of charm particles produced at the LHC.

But why is this important? To understand why the universe produced less antimatter than matter we need to learn more about the asymmetry in the production of the two, a process known as CP-violation. It has already been shown that some unstable particles decay in a different way to their corresponding antimatter particle. This may have contributed to the abundance of matter in the universe,with previous discoveries of it leading to Nobel Prizes.

We also want to find CP-violation in the process of mixing. If we start with millions of D0 particles and millions of D0 antiparticles, will we end up with more D0 normal matter particles after some time? Knowing the oscillation rate is a key step towards this goal. While we did not find an asymmetry this time, our result and further precision measurements can help us find it in the future.

Next year, the LHC will switch on after a long shut down and the new upgraded LHCb detector will take much more data, boosting the sensitivity of these measurements further. Meanwhile, theoretical physicists are working on new calculations to interpret this result. The LHCb physics program will also be complemented by the Belle-II experiment in Japan. These are exciting prospects for investigating matter-antimatter asymmetry and the oscillations of mesons.

While we cannot yet completely solve the mysteries of the universe, our latest discovery has put the next piece in the puzzle. The new upgraded LHCb detector will open the door to an era of precision measurements that have the potential to uncover yet unknown phenomena, and perhaps physics beyond the Standard Model.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Image Credit: motionstock from Pixabay

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CERN: How We're Probing the Universe's Origins Using Record Precision Measurements - Singularity Hub