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This paper describes some of the latest features in the commercial electromagnetic software Feko (including WinProp). These include the modeling of non-ideal cable shield connections, the parallel direct adaptive cross approximation (ACA) solver, edge and wedge diffraction for the ray launching geometrical optics (RL-GO) solver, and several new features related to automotive radar.

This paper describes recent advances of the commercial CEM code FEKO, as well as the wave propagation and radio network planning tool WinProp. This includes the simulation of characterized surfaces (complex radomes, frequency-selective surfaces) with RL-GO, a direct solver for ACA (adaptive cross approximation), and supporting FEM (finite element method) and MoM (method of moments) with SEP (surface equivalence principle) in the same model.

This paper describes new features to the electromagnetic simulation software FEKO as introduced in the FEKO 2018 version. These include the GPU support for the RL-GO (ray launching geometrical optics) solver, a direct solver for ACA (adaptive cross approximation), and various cable modeling extensions.

This paper summarises the latest extensions to the electromagnetic field solver package FEKO. Advanced parallelisation options for full wave methods (MLFMM, FDTD), speed improvements for cable harness modelling, extensions to the asymptotic RL-GO solver, and improved mode tracking for CMA are discussed.

Reducing the production impact on the cooling load is pertinent in minimizing overall energy usage within the manufacturing environment. This paper expands upon previous research to analyze the complex energy dynamics of the production line and evaluate the effect of the production on the cooling load for the heating, ventilation, and air conditioning system. The radiant time series method is utilized to estimate the radiative heat load, which allows for the calculation of the cooling load caused by each individual machine on the production line. To reduce the overall cooling load, an opportunity window control scheme is employed that allows for certain machines to be turned off without affecting production. This control scheme leads to a reduction in energy consumption and cooling load for the manufacturing facility. Simulation studies are performed using Simulink/MATLAB to validate the cooling load analysis and the opportunity window control methodology.

Since the Brilliant wind platform was launched in early 2013, GE has developed and commercialized a host of hardware and software features to increase wind farm Annual Energy Production, improve services productivity, and open up new customer revenue streams. By utilizing advanced control algorithms and analytics coupled with deep domain expertise in power electronics and grid integration, GE is creating more with less - getting more power and efficiency out of existing hardware, taking an inherently variable wind resource and integrating it more smoothly onto the grid, managing the complexity of multiple turbines within a farm and multiple farms within a grid system, and making wind predictable and reliable even in areas with weak infrastructure. By harnessing the power of the industrial internet GE will continue to develop innovative features within the Brilliant wind platform, transforming the wind industry as we tackle the next generation of challenges and opportunities.

The smart grid is a rapidly emerging field that aims to modernize the distribution and delivery of electricity, water and gas utilities. A key component in the smart grid is the smart meter, which is installed at utility endpoints for usage monitoring and billing. Currently electric meters have received the majority of research attention and focus. However, smart gas meters will also play an important role in the emerging smart grid. This paper presents a high-resolution automated gas meter reading system for residential households. The system can be used to non-intrusively monitor the natural gas consumption of individual appliances in a home. It is implemented by utilizing an existing gas meter retrofitted with a module that includes a high-resolution encoder to collect gas flow data and a microprocessor to analyze and identify appliance load profiles. Additional benefits of the system include the ability to detect very small leaks and theft, perform efficiency analyses, and provide real time customer feedback on gas usage.

This paper presents the design and implementation of a high-resolution automated metering system for a residential natural gas meter. This new high resolution sensing technique can non-intrusively monitor the gas consumption of individual appliances in a home by resolving small amounts of gas usage. It relies on utilizing an existing meter that will be retrofitted with a module that includes a high-resolution encoder to collect gas flow data and a microprocessor to analyze and identify ap-pliance load profiles. Additional benefits of the system include the ability to detect very small leaks and theft, efficiency analysis, and real time customer feedback of gas usage. The system has the potential for wide scale market adoption.

Today's 3rd generation CT scanners have one or two X-ray tubes, with one focal spot or “source” per vacuum chamber or “tube”. Our first multi-source inverse geometry CT prototype has eight X-ray sources. We have demonstrated multisource imaging with an 8-spot X-ray tube on a stationary gantry and a rotating phantom. We present an update on the development of the gantry-based multi-source CT scanner: we combine the multi-source X-ray tube and gantry rotation producing the first multi-source gantry-based CT scanner prototype. Currently the system is in the process of being upgraded to 32 X-ray sources to provide a larger field-of-view and to demonstrate the concept of virtual bowtie.

Third-generation CT architectures are approaching fundamental limits. Dose-efficiency is limited by finite detector efficiency and by limited control over the X-ray flux spatial profile. Increasing the volumetric coverage comes with increased scattered radiation, cone-beam artifacts, Heel effect, wasted dose and cost. Spatial resolution is limited by focal spot size and detector cell size. Temporal resolution is limited by mechanical constraints, and alternative geometries such as electron-beam CT and dual-source CT come with severe tradeoffs in terms of image quality, dose-efficiency and complexity. The concept of multi-source inverse-geometry CT (IGCT) breaks through several of the above limitations [1-3], promising a low-dose high image quality volumetric CT architecture. In this paper, we present recent progress with the design and integration efforts of the first gantry-based multi-source CT scanner.

The ability to control marrow stromal cell (MSC) differentiation towards osteoblasts could potentially play a key role in bone regeneration. Here we examine the efficacy of the photoacoustic (PA) effect enhanced by the presence of single-walled carbon nanotubes (SWNTs) on the differentiation of MSCs. We report that MSCS in the presence or absence of SWNTs exposed to brief PA stimulation (10 mins daily) using a nanosecond pulse-laser over a period 16 consecutive days have increased osteodifferentiation.

A domain decomposition procedure is described that reduces the memory required to solve large finite-elements problems. The procedure involves partitioning a large computational domain into several smaller domains and solving the subdomain problems iteratively. Robin boundary conditions are used at the interfaces between domains to ensure correct field behavior across subdomain boundaries. The procedure and memory savings are illustrated with the analysis of a Rotman lens with and without domain decomposition.

There has been an increased interest recently in the Rotman lens as a feed structure for phased array. These antennas/feed structures need to be easy to implement, be cost effective, provide for rapid beam scan across wide angles and be reliable in a sometimes harsh environment. The Rotman lens meets these requirements. Special purpose codes have been written to analyze a limited set of lens implementations and they are very efficient (Singhal, P.K. et al., 1998), but they are not general enough to analyze such electrically large devices in their many possible configurations. For a complete model with tight accuracy requirements, the number of unknowns would increase significantly and a different approach may be more effective. We believe that the domain decomposition method (DDM) may be such an approach. We discuss the basics of this procedure, how it is used to analyze a Rotman lens and conclude with a simplified lens example.

We propose a mathematically equivalent formulation but computationally more efficient than the one used in Vouvakis et al. (2004). It is formulated in a way that the traditional programs for the curl-conforming finite element method can be used without further modification. The field continuity between the mismatching meshes on the interfaces is imposed through a supplementary equation derived front the Robin boundary condition. To achieve high-order accuracy and subdue the numerical dispersion, we employ a high-order curl-conforming vector basis. We study the effects of mismatching meshes and the orders of basis vectors on the solution accuracy and iteration counts, and examine how the sequences of solving subdomain problems affect the iteration counts, and formulate when the elimination of interior unknowns leading to a smaller dense matrix is advantageous.

Novel temperature sensors for harsh environments have been fabricated using thermal spray technology. Concepts for strain sensors fabricated with thermal spray technology are also being developed. This work reports on functional thermocouples and strain gauge concepts fabricated using this novel application of thermal spray processing.

The series of firing times from a neuron can be viewed as a point process. There is great interest in being able to relate these firing times to dynamical variables such as the intracellular voltage. A method has recently been proposed (T. Saner, Phys. Rev. Let., vol. 72, p. 3811, 1994) that allows the reconstruction of the full dynamics of an input to an integrate and fire (IF) device using a delay embedding of interspike intervals (ISI's). The authors show that this does not imply that the intracellular dynamics of a neuron can be reconstructed. They use a similar but physiologically more plausible IF neuron model to show that the attractor can only be reconstructed if the dynamics are "sampled" at a high frequency by the spikes. The reconstructed dynamics degrade for more physiologically plausible sampling rates.

Nonlinear delay-differential equations (DDE's) commonly appear in models of physiological and neural control. In certain parameter ranges, for example in chaotic regimes, such equations have unstable periodic orbits (UPO's). Furthermore, these equations exhibit multistability when the delay to response time ratio is significantly greater than one. We first show that the UPO's can be stabilized using a second delayed feedback control. We then show that the controlled solutions are multistable. This enables us to encode a finite string of bits into a particular waveform of an unstable periodic solution. Our results indicate that it is possible to control the time evolution of DDE's using appropriate initial functions.

Studies the storage of information in recurrent neural feedback circuits modeled by nonlinear delay-differential equations (DDE's). The information is encoded into the initial function from which the DDE evolves into a periodic solution. We find that the Mackey-an der Heiden (MH) model of recurrent inhibition (RI), involving non-spiking neurons, has multistable periodic patterns of voltage, and thus of spike patterns. The spiking solutions of Plant's model, based on the Fitzhugh-Nagumo equations, are also found to be encodable. Our approach offers a simple mechanism for active short-term memory based on the temporal patterns of a simple neural system rather than on the spatial properties of a neural network.