MIT News’s picture

By: MIT News

Buildings account for about 40 percent of U.S. energy consumption, and are responsible for one-third of global carbon dioxide emissions. Making buildings more energy-efficient is not only a cost-saving measure, but also a crucial climate-change mitigation strategy. Hence the rise of “smart” buildings, which are increasingly becoming the norm around the world.

Smart buildings automate systems like heating, ventilation, and air conditioning (HVAC), lighting, electricity, and security. Automation requires sensory data, such as indoor and outdoor temperature and humidity, carbon dioxide concentration, and occupancy status. Smart buildings leverage data in a combination of technologies that can make them more energy-efficient.

Since HVAC systems account for nearly half of a building’s energy use, smart buildings use smart thermostats, which automate HVAC controls and can learn the temperature preferences of a building’s occupants.

Loretta Marie Perera’s picture

By: Loretta Marie Perera

Recently, the team at 4C Creative Cad CAM Consultants in Emmen, Netherlands, was given a unique task: How to get a vintage Harley Davidson motorcycle back on the road again.

What was fun about this project wasn’t how challenging it was, or how much expertise it required. The joy was in the end itself, to provide a straightforward solution to a question that had been on the mind of one man for decades: How to get his vintage motorcycle capable of starting and riding on the streets. The solution was to scan a broken part that could no longer be found and 3D print a replacement.

The problem was brought to Carl van de Rijzen of Visual First in the Netherlands, who has been working with Edwin Rappard of 4C Creative CAD CAM Consultants for more than two years. Living on opposite ends of the country, the two have never met in person. “I send something to Edwin, he scans it and sends it back,” says van de Rijzen. The same thing occurred in this case.

NVision Inc.’s picture

By: NVision Inc.

NVision’s engineering services are helping managers of coal-fired power plants converting to natural gas to determine more quickly where to install updated instrumentation necessary to retrofit turbines to accommodate the new power source.

“By measuring the equipment via laser scanning, then creating precise 3D models of the turbine assemblies for engineers to analyze for optimal installation points, we can significantly expedite the plants’ transitions,” says Steve Kersen, president of NVision. “This can result in huge cost savings for projects that would otherwise have been budgeted for a lengthier period using less sophisticated measurement methods. In one recent project, a Southeast power plant converting to a combined-cycle gas turbine (CCGT*) system will increase wattage output by more than 30 percent and save more than $250,000 by using our services.”

Douglas Allen’s picture

By: Douglas Allen

Any number derived from real observation is made up of three components. The first of these is the intended signal, the “perfect” value from the object being observed. The second is error (or noise) caused by environmental disturbance and/or interference. The third is bias, a regular and consistent deviation from the perfect value.

O = S + N + B, or observation equals signal plus noise plus bias

The signal usually is predictably constant, as is the bias. Identifying and eliminating bias requires a set of techniques beyond the scope of this article, so for the remainder of this, we will consider both as components of the signal, leaving a somewhat simpler equation for our observation.

O = S + N, or observation equals signal plus noise

This article focuses on removing the random noise component from the observation and leaving the signal component. The noise is in the form of chance variation, which sometimes enhances the signal and sometimes detracts from it. If we could separate the noise from the signal and eliminate it, our observation would be pure signal, or a precise and consistent value.

Lawrence Livermore National Laboratory’s picture

By: Lawrence Livermore National Laboratory

A team of Lawrence Livermore National Laboratory (LLNL) scientists has simulated the droplet-ejection process in an emerging metal 3D-printing technique called “liquid metal jetting” (LMJ), a critical aspect to the continued advancement of liquid metal printing technologies.

In their paper, which was published in the journal Physics of Fluids, the team describes the simulating of metal droplets during LMJ, a novel process in which molten droplets of liquid metal are jetted from a nozzle to 3D-print a part in layers. The process does not require lasers or metal powder and is more similar to inkjet printing techniques.

Using the model, researchers studied the primary breakup dynamics of the metal droplets, essential to improving the understanding of LMJ. LMJ has advantages over powder-based approaches in that it provides a wider material set and does not require production or handling of potentially hazardous powders, researchers said.

Loretta Marie Perera’s picture

By: Loretta Marie Perera

A steam train not seen since the 1960s is being rebuilt by a group of engineering enthusiasts, assisted by the metrology experts at the University of Sheffield Advanced Manufacturing Research Centre (AMRC). With a little extra help from Hexagon’s advanced industrial laser tracker technology, the team got the measure of a mysterious discrepancy between the original drawings and the actual locomotive.

The Standard Steam Locomotive Co. group has set itself the ambitious challenge to recreate, operate, and maintain a lost class of British steam train—a British Railways’ Standard Class 6 “Clan”—using a combination of the original 1950s design drawings and 21st-century engineering. The plan is to incorporate modern design and manufacturing techniques and technologies into the build.

Jérôme-Alexandre Lavoie’s picture

By: Jérôme-Alexandre Lavoie

With the increasing popularity of electric vehicles (EV), a lot of engineers and quality control specialists are facing new challenges when inspecting parts. Whereas traditional cars had primarily mechanical parts, EVs now feature complex electrical-mechanical devices controlled by software. Although they have fewer moving parts than gasoline vehicles, EVs have myriad complicated subsystems—all of which affect the performance and handling of these vehicles.

In order to improve product safety and production throughput, more EV manufacturers are turning to automated quality control systems in plants and right on their production floors. Anomalies can be instantaneously reported back to the engineering staff for quick corrective measures. Speeding up inspections leads to more throughput and a faster time to market.

Inefficient quality control, lack of skilled labor slow throughput

In today’s tough labor market, there is a clear lack of skilled labor with the experience and expertise required to perform effective quality control inspections.

Judith Su’s picture

By: Judith Su

My Little Sensor Lab at the University of Arizona develops ultrasensitive optical sensors for medical diagnostics, medical prognostics, environmental monitoring, and basic science research. Our sensor technology identifies substances by shining light on samples and measuring the index of refraction, or how much light is slowed down when it passes through a material that is different from one substance to another—say, water and a DNA molecule.

The big idea

Our technology lets us detect extremely low concentrations of molecules down to one in a million-trillion molecules and can give results in under 30 seconds.

Ordinarily, index of refraction is too subtle to detect in a single molecule, but using a technology we developed, we can pass light through a sample thousands of times, which amplifies the change. This makes our sensor among the most sensitive in existence.

The device includes a tiny ring that light races around—240,000 times in 40 nanoseconds, or billionths of a second. A liquid sample surrounds the sensor. Some of the light extends outside of the ring, where it interacts with the sample thousands of times.

Elizabeth Benham’s picture

By: Elizabeth Benham

This year will be the 45th anniversary of the Metric Conversion Act, which was signed on Dec. 23, 1975, by President Gerald R. Ford. Normally, we celebrate by sharing metric education resources, but this year I want to use the occasion to dispel some common misconceptions about the U.S. relationship with the metric system.

You’ve probably heard that the United States, Liberia, and Burma (aka Myanmar) are the only countries that don’t use the metric system (International System of Units or SI). You may have even seen a map that has been incriminatingly illustrated to show how they are out of step with the rest of the world.


Countries that have not "officially" adopted the metric system (The United States, Myanmar, and Liberia) in gray. Credit: AzaToth [Public domain], via Wikimedia Commons

 

George Schuetz’s picture

By: George Schuetz

Before a fixture gauge is designed, the engineer must understand what specifications must be inspected. In many respects, the gauge’s design reflects not only the design of the part but also the manufacturing processes that produced it.

Machinists must establish datums in order to machine a part accurately, and gauge designers often need to know what those datums are in order to position the part repeatably relative to the gauge head or other sensitive device. Sounds simple and straightforward, but that is not always the case.

Sometimes the parts are so large that they cannot easily be brought to the gauge, and a special arrangement might be required to bring the gauge to a section of the part. Other times, the part is so small that it seems impossible to get to the dimension that must be measured. Gauge designers are always amused when a part print—that comes in at 10 times the normal size—refers to a small land at the bottom of the bore. At 10 times the size, it looks pretty simple, although in reality it may be impossible to measure.

This is when good fixture design comes into play to ensure the measurement can be made in a way that is easy for the operator to make, and to produce repeatable and accurate results.

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