Utsumi M.,HI Corporation |
Utsumi M.,Technical Machine
AIAA Journal | Year: 2017
The damping ratio oflow-gravity sloshing induced by the friction work duetocontact angle hysteresis is calculated using a newly developed semianalytical sloshing analysis method for arbitrary axisymmetric tanks. The damping ratio is estimated for the first mode for the case with small contact angle and its variation, as a fundamental study for propellant sloshing. First, the relation between the friction force and the changein the contact angle causedby contact angle hysteresis is derived from the equilibrium among the friction force and the three surface tensions. Next, the virtual work donebythe friction forceis calculatedto determine the nonlinear damping termtobeintroduced into the modal equation for sloshing. Physical considerations are made for the dependencies of the damping ratio on the Bond number and filling level. Although the damping term arises from the second-order small term in the friction force, the damping ratio can reach the same order as the viscous damping ratio for low Bond numbers because, due to the hysteresis nonlinearity, the friction damping ratio increases with decreasing Bond number more markedly than the viscous ratio. © Copyright 2016 by Joseph I. Milluzzo III and J. Gordon Leishman.
Huang Y.,City University of New York |
Parra L.C.,City University of New York |
Haufe S.,Columbia University |
Haufe S.,Technical Machine
NeuroImage | Year: 2016
In source localization of electroencephalograpic (EEG) signals, as well as in targeted transcranial electric current stimulation (tES), a volume conductor model is required to describe the flow of electric currents in the head. Boundary element models (BEM) can be readily computed to represent major tissue compartments, but cannot encode detailed anatomical information within compartments. Finite element models (FEM) can capture more tissue types and intricate anatomical structures, but with the higher precision also comes the need for semi-automated segmentation, and a higher computational cost. In either case, adjusting to the individual human anatomy requires costly magnetic resonance imaging (MRI), and thus head modeling is often based on the anatomy of an ‘arbitrary’ individual (e.g. Colin27). Additionally, existing reference models for the human head often do not include the cerebro-spinal fluid (CSF), and their field of view excludes portions of the head and neck—two factors that demonstrably affect current-flow patterns. Here we present a highly detailed FEM, which we call ICBM-NY, or “New York Head”. It is based on the ICBM152 anatomical template (a non-linear average of the MRI of 152 adult human brains) defined in MNI coordinates, for which we extended the field of view to the neck and performed a detailed segmentation of six tissue types (scalp, skull, CSF, gray matter, white matter, air cavities) at 0.5 mm 3 resolution. The model was solved for 231 electrode locations. To evaluate its performance, additional FEMs and BEMs were constructed for four individual subjects. Each of the four individual FEMs (regarded as the ‘ground truth’) is compared to its BEM counterpart, the ICBM-NY, a BEM of the ICBM anatomy, an ‘individualized’ BEM of the ICBM anatomy warped to the individual head surface, and FEMs of the other individuals. Performance is measured in terms of EEG source localization and tES targeting errors. Results show that the ICBM-NY outperforms FEMs of mismatched individual anatomies as well as the BEM of the ICBM anatomy according to both criteria. We therefore propose the New York Head as a new standard head model to be used in future EEG and tES studies whenever an individual MRI is not available. We release all model data online at neuralengr.com/nyhead/ to facilitate broad adoption. © 2015
Chiotellis S.,Technical Machine |
Grismajer M.,Technical Machine
Leveraging Technology for a Sustainable World - Proceedings of the 19th CIRP Conference on Life Cycle Engineering | Year: 2012
In-process monitoring of the electrical power of manufacturing equipment has become technologically and economically viable and is essential in capturing the energy consumption behaviour of manufacturing systems in relation to operations. A concept for real-time analysis of electrical power, based on data stream analysis and event-driven system approaches has been developed and implemented as a software application. Electrical power data is handled in the form of streaming time series and are statistically analysed and transformed in compact, information rich representations in real-time. The developed prototype is validated on the example of a milling machine.
Tolstikhin K.,Technical Machine
Journal of Engineering Mathematics | Year: 2016
The problem of differentiating non-smooth functions of specimen displacements, which are measured during the material removal, is discussed. This problem arises when employing the layer removal method, namely a method of rings and strips, for residual stress depth profiling. It is shown that this problem is ill-posed and special solution methods are required in order to obtain a stable solution. The stability of the solution affects to a high extent the resulting accuracy of the residual stress evaluation in the investigated material. The presented study discusses a numerical approach to solving such ill-posed problems. The proposed approach, which is based on the Tikhonov regularization and a regularized finite difference method, provides a stable approximate solution, including its pointwise error estimation. The advantage of this approach is that it does not require any knowledge about the unknown exact solution; the pointwise error estimation of the measured data is the only prior information that must be available. In addition, this approach provides a convergence of the approximate solution to the unknown exact one when the perturbation of the initial data approaches zero. © 2016 Springer Science+Business Media Dordrecht
Winczek J.,Technical Machine
Journal of Materials Processing Technology | Year: 2012
In this paper computational methodology of elasto-plastic states for rods subjected to thermal loads is presented. The dependence of stresses on strain was assumed on the basis of tension curves taking into account temperature. The computations of strains and stresses in a rod made of S235 steel, loaded by thermal fields generated by a point welding heat source of different intensities, were investigated. The analysis of development of plastic strains was carried out. Experimental tests were made for surfaced rod, with geometry and welding parameters assumed in numerical simulations, to verify the correctness of modelling. A simplified method was proposed to determine the longitudinal stresses in surfaced rods. © 2012 Elsevier B.V.
News Article | March 5, 2015
Technical Machine, a startup making a development boards for the internet of things, has launched a second generation product that has more power and better Wi-Fi. The Tessel 2 goes on sale today for $35 and will act more as a hub device mediating the inputs from a variety of sensors or other inputs. The board will ship in August. Jon McKay, the CEO of Technical Machine, said in a few weeks the company plans to launch a lower-power version of a Tessel 2 board that will function more like a sensor device. The idea of the board is to get web developers more accustomed to playing with code, comfortable taking their ideas for software and bringing them into the real world. With both Tessel boards they can now connect the web to a physical device — be it a sensor or something a bit more complicated like a display. McKay says companies such as Azure and SAP are using the boards in their data centers while other customers such as a doctor trying to prototype a wearable device and a company trying to increase insect protein production are also using the boards. The companies building prototypes are a big market for the Tessel 2 and one that McKay is trying to better serve with this iteration. McKay designed the board to make it easier and cheaper to take it into limited production of a hundred to a couple thousand items, such as making sure that unused sections of the boards can be broken off to avoid wasting space, you can integrate modules into the PCB so they the connectors or more secure. These efforts are part of several being attempted by companies in the burgeoning hardware sector to make manufacturing and prototyping easier. For example, when I covered the partnership between SnapEDA and Octopart I wrote: With the emergence of startups like the Toronto-based SnapEDA or the YCombinator startup Octopart, we’re seeing the evolution of hardware development that aims to be a bit more like software. Faster, more iterative and more responsive to the needs of a rapidly-changing marketplace. We won’t ever get to the speed of code, but it’s awesome to see the agility that’s common in software creeping its way into the hardware world as much as it can. With Tessel 2, programmers now can use these boards (currently they can program Tessel 2 in Node.js/io.js) to take their ideas for new hardware and turn them into reality without having to spent a lot of time learning a lot about hardware. The steps the Technical Machine team has taken to make getting prototypes to production easier means that the software developers using the boards get an even longer runway when it comes to learning about hardware. This will only help let good ideas mature a bit further and broaden the scope of what the internet of things will make possible. Technical Machine is backed by True Ventures, a venture capital firm that is an investor in the parent company of Gigaom.
News Article | December 4, 2013
News Article | October 7, 2013
News Article | March 5, 2015
Building on the success of its flagship product Tessel, released last May, Technical Machine is introducing Tessel 2, an enterprise-grade embedded hardware platform that enables software developers to easily create Web-connected devices, including everything from Internet-enabled manufacturing equipment to self-watering plants. “We’ve seen a ton of interest from engineers outside the traditional embedded industry who want to build products with a hardware component,” said Jon McKay, co-founder of Technical Machine. “Prototyping tools such as Tessel have been getting easier to use but scaling a product is still really difficult. Tessel 2 enables this quickly growing user base to start scaling hardware products even without electrical engineering expertise, and without investing the time and cost you might need with traditional processes like consulting shops.” Founded in September 2013, Technical Machine raised nearly $200,000, almost four times its original goal of $50,000, through an online crowdfunding campaign in October 2013. The following month, the company secured more than $1M in a funding round led by True Ventures. Technical Machine sold thousands of original Tessel units to customers that include SAP, Microsoft, and Intuit. “We see a huge untapped market for all kinds of ‘Internet of Things’ goods,” said Rohit Sharma, venture partner with True Ventures, the company’s lead investor. “The challenge is that Web developers can write the code to run those items, but lack the electrical engineering expertise to build the hardware. The Tessel platform makes it easy for entrepreneurial Web developers to create connected devices inexpensively and efficiently, and Tessel 2 lets them take those devices into production.” Tessel 2, less than half the cost of its predecessor at volume, is designed to be embeddable at scale. It offers the ability to only populate parts of the board that are needed, and to integrate Tessel Modules into the circuit board instead of using connectors. The result is a cost-effective, integrated printed circuit board that enables customers to get to market faster and cheaper than ever before. Tessel 2 features robust built-in Wifi and a completely compatible Node.js/io.JS runtime. Tens of thousands of Node software libraries can be used out of the box. Tessel 2 uses plug-and-play hardware modules including temperature sensors, cameras, and servo motors, etc. The team plans to support Rust and other languages soon after ship. Analysts expect interest and demand for Web-enabled devices to skyrocket during the next few years: Gartner estimates 26 billion devices will be created by 2020. What’s more, 62 percent of SMBs say they’ve dedicated budget to develop Internet of Things products this year. “With its open and scalable platform for hardware development, Technical Machine is positioned to help drive and support business growth and creation as more companies push to develop these web-connected devices,” added Sharma from True Ventures. In addition to McKay, Technical Machine’s co-founders are Tim Ryan, Chief Product Officer, and Jia Huang, Chief Operations Officer. Customers can pre-order V2 Tessel here for $35, and less at scale. Shipping is slated for August 2015. About Technical Machine Headquartered in Berkeley, Calif. and backed by True Ventures, Slow Ventures, Rough Draft VC and angel investors Karl Jacob and Drew Volpe, Technical Machine is a developer tools company, building an open and scalable platform for hardware development. Bridging the gap between web development and hardware production, Technical Machine is capitalizing on the $310B market opportunity for hardware, software and services supporting the Internet of Things.