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At least 1,315 records · Page 73

Texas Hydrogen Highway Fuel Cell Hybrid Bus and Fueling Infrastructure Technology Showcase (Final Scientific/Technical Report)

The Texas Hydrogen Highway project has showcased a hydrogen fuel cell transit bus and hydrogen fueling infrastructure that was designed and built through previous support from various public and private sector entities. The aim of this project has been to increase awareness among transit agencies and other public entities on these transportation technologies, and to place such technologies into commercial applications, such as a public transit agency. The initial project concept developed in 2004 was to show that a skid-mounted, fully-integrated, factory-built and tested hydrogen fueling station could be used to simplify the design, and lower the cost of fueling infrastructure for fuel cell vehicles. The approach was to design, engineer, build, and test the integrated fueling station at the factory then install it at a site that offered educational and technical resources and provide an opportunity to showcase both the fueling station and advanced hydrogen vehicles. The two primary technology components include: Hydrogen Fueling Station: The hydrogen fueling infrastructure was designed and built by Gas Technology Institute primarily through a funding grant from the Texas Commission on Environmental Quality. It includes hydrogen production, clean-up, compression, storage, and dispensing. The station consists of a steam methane reformer, gas clean-up system, gas compressor and 48 kilograms of hydrogen storage capacity for dispensing at 5000 psig. The station is skid-mounted for easy installation and can be relocated if needed. It includes a dispenser that is designed to provide temperature compensated fills using a control algorithm. The total station daily capacity is approximately 50 kilograms. Fuel Cell Bus: The transit passenger bus built by Ebus, a company located in Downey, CA, was commissioned and acquired by GTI prior to this project. It is a fuel cell plug-in hybrid electric vehicle which is ADA compliant, has air conditioning sufficient for Texas operations, and regenerative braking for battery charging. It uses a 19.3 kW Ballard PEM fuel cell, will store 12.6 kg of hydrogen at 350 Bar, and includes a 60 kWh battery storage system. The objectives of the project included the following: (a) To advance commercialization of hydrogen-powered transit buses and supporting infrastructure; (b) To provide public outreach and education by showcasing the operation of a 22-foot fuel cell hybrid shuttle bus and Texas first hydrogen fueling infrastructure; and (c) To showcase operation of zero-emissions vehicle for potential transit applications. As mentioned above, the project successfully demonstrated an early vehicle technology, the Ebus plug-in hybrid fuel cell bus, and that success has led to the acquisition of a more advanced vehicle that can take advantage of the same fueling infrastructure. Needed hydrogen station improvements have been identified that will enhance the capabilities of the fueling infrastructure to serve the new bus and to meet the transit agency needs. Over the course of this project, public officials, local government staff, and transit operators were engaged in outreach and education activities that acquainted them with the real world operation of a fuel cell bus and fueling infrastructure. Transit staff members in the Dallas/Ft. Worth region were invited to a workshop in Arlington, Texas at the North Central Texas Council of Governments to participate in a workshop on hydrogen and fuel cells, and to see the fuel cell bus in operation. The bus was trucked to the meeting for this purpose so that participants could see and ride the bus. Austin area transit staff members visited the fueling site in Austin to be briefed on the bus and to participate in a fueling demonstration. This led to further meetings to determine how a fuel cell bus and fueling station could be deployed at Capital Metro Transit. Target urban regions that expressed additional interest during the project in response to the outreach meetings and showcase events include San Antonio and Austin, Texas. In summary, the project objectives were achieved in the following ways: Through presentations and papers provided to a variety of audiences in multiple venues, the project team fulfilled its goal of providing education and outreach on hydrogen technology to statewide audiences. The project team generated interest that exists well beyond the completion of the project, and indeed, helped to generate financial support for a subsequent hydrogen vehicle project in Austin. The University of Texas, Center for ElectroMechanics operated the fuel cell-electric Ebus vehicle for over 13,000 miles in Austin, Texas in a variety of routes and loading configurations. The project took advantage of prior efforts that created a hydrogen fueling station and fuel cell electric-hybrid bus and continued to verify their technical foundation, while informing and educating potential future users of how these technologies work.

03 NATURAL GAS↗

Viscous simulation method for unsteady flows past multicomponent configurations

The present algorithm for the numerical simulation of flows about complex configurations (whose multiple and nonsimilar components have arbitraty geometries) employs a hybridization of the domain decomposition techniques for grid generation as well as to reduce computer-memory requirements. A fully vectorized, finite-volume, upwind-biased, approximately factored multigrid method is used to solve 3D Reynolds-averaged unsteady and compressible Navier-Stokes equations simulating supersonic flows past an ogive-nose-cylinder near or within a cavity. The time-averaged surface pressures obtained compare favorably with the wind tunnel data.

Fouladi, Kamran↗

Interactive Terascale Particle Visualization

This paper describes the methods used to produce an interactive visualization of a 2 TB computational fluid dynamics (CFD) data set using particle tracing (streaklines). We use the method introduced by Bruckschen et al. [2001] that pre-computes a large number of particles, stores them on disk using a space-filling curve ordering that minimizes seeks, and then retrieves and displays the particles according to the user's command. We describe how the particle computation can be performed using a PC cluster, how the algorithm can be adapted to work with a multi-block curvilinear mesh, and how the out-of-core visualization can be scaled to 296 billion particles while still achieving interactive performance on PG hardware. Compared to the earlier work, our data set size and total number of particles are an order of magnitude larger. We also describe a new compression technique that allows the lossless compression of the particles by 41% and speeds the particle retrieval by about 30%.

Ellsworth, David↗

Simulation-driven optimization of high-order meshes in ALE hydrodynamics

Here we propose tools for high-order mesh optimization and demonstrate their benefits in the context of multi-material Arbitrary Lagrangian-Eulerian (ALE) compressible shock hydrodynamic applications. The mesh optimization process is driven by information provided by the simulation which uses the optimized mesh, such as shock positions, material regions, known error estimates, etc. These simulation features are usually represented discretely, for instance, as finite element functions on the Lagrangian mesh. The discrete nature of the input is critical for the practical applicability of the algorithms we propose and distinguishes this work from approaches that strictly require analytical information. Our methods are based on node movement through a high-order extension of the Target-Matrix Optimization Paradigm (TMOP). The proposed formulation is fully algebraic and relies only on local Jacobian matrices, so it is applicable to all types of mesh elements, in 2D and 3D, and any order of the mesh. We discuss the notions of constructing adaptive target matrices and obtaining their derivatives, reconstructing discrete data in intermediate meshes, node limiting that enables improvement of global mesh quality while preserving space-dependent local mesh features, and appropriate normalization of the objective function. The adaptivity methods are combined with automatic ALE triggers that can provide robustness of the mesh evolution and avoid excessive remap procedures. The benefits of the new high-order TMOP technology are illustrated on several simulations performed in the high-order ALE application BLAST.

97 MATHEMATICS AND COMPUTING↗

Concepts for on board satellite image registration. Volume 4: Impact of data set selection on satellite on board signal processing

The NASA NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. This volume addresses the impact of data set selection on data formatting required for efficient telemetering of the acquired satellite sensor data. More specifically, the FILE algorithm developed by Martin-Marietta provides a means for the determination of those pixels from the data stream effects an improvement in the achievable system throughput. It will be seen that based on the lack of statistical stationarity in cloud cover, spatial distribution periods exist where data acquisition rates exceed the throughput capability. The study therefore addresses various approaches to data compression and truncation as applicable to this sensor mission.

Ruedger, W. H.↗

A solution procedure for behavior of thick plates on a nonlinear foundation and postbuckling behavior of long plates

Approximate solutions for three nonlinear orthotropic plate problems are presented: (1) a thick plate attached to a pad having nonlinear material properties which, in turn, is attached to a substructure which is then deformed; (2) a long plate loaded in inplane longitudinal compression beyond its buckling load; and (3) a long plate loaded in inplane shear beyond its buckling load. For all three problems, the two dimensional plate equations are reduced to one dimensional equations in the y-direction by using a one dimensional trigonometric approximation in the x-direction. Each problem uses different trigonometric terms. Solutions are obtained using an existing algorithm for simultaneous, first order, nonlinear, ordinary differential equations subject to two point boundary conditions. Ordinary differential equations are derived to determine the variable coefficients of the trigonometric terms.

Stein, M.↗

A locally implicit method for fluid flow problems

The fluid flow inside the space shuttle main engine (SSME) traverses through a complex geometrical configuration. The flow is compressible, viscous, and turbulent with pockets of separated regions. Several computer codes are being developed to solve three dimensional Navier-Stokes equations with different turbulence models for analyzing the SSME internal flow. The locally implicit scheme is a computationally efficient scheme which converges rapidly in multi-grid modes for elliptic problems. It has the promise of providing a rapidly converging algorithm for steady-state viscous flow problems.

Reddy, K. C.↗

An explicit Runge-Kutta method for turbulent reacting flow calculations

The paper presents a numerical method for the solution of the conservation equations governing steady, reacting, turbulent viscous flow in two-dimensional geometries, in both Cartesian and axisymmetric coordinates. These equations are written in Favre-averaged form and closed with a first order model. A two-equation K-epsilon model, where low Reynolds number and compressibility effects are included, and a modified eddy-break up model are used to simulate fluid mechanics turbulence, chemistry and turbulence-combustion interaction. The solution is obtained by using a pseudo-unsteady method with improved perturbation propagation properties. The equations are discretized in space by using a finite volume formulation. An explicit multi-stage dissipative Runge-Kutta algorithm is then used to advance the flow equations in the pseudo-time. The method is applied to the computation of both diffusion and premixed turbulent reacting flows. The computed temperature distributions compare favorably with experimental data.

Boretti, A. A.↗

Pipeline synthetic aperture radar data compression utilizing systolic binary tree-searched architecture for vector quantization

A system for data compression utilizing systolic array architecture for Vector Quantization (VQ) is disclosed for both full-searched and tree-searched. For a tree-searched VQ, the special case of a Binary Tree-Search VQ (BTSVQ) is disclosed with identical Processing Elements (PE) in the array for both a Raw-Codebook VQ (RCVQ) and a Difference-Codebook VQ (DCVQ) algorithm. A fault tolerant system is disclosed which allows a PE that has developed a fault to be bypassed in the array and replaced by a spare at the end of the array, with codebook memory assignment shifted one PE past the faulty PE of the array.

Chang, Chi-Yung↗

Detecting Process Equipment Failures Using Acoustic Data and Machine Learning

Nuclear power plant (NPP) process equipment such as fans, motors, valves, and pumps generate frequent or continuous noise, and deviations from the normal operational sounds made by this equipment can indicate potential issues. These deviations can be identified via automated acoustic anomaly detection, which involves using acoustic sensors (i.e., microphones) alongside detection algorithms to continuously monitor for changes in acoustic signatures. This task is made challenging by the substantial background noise that exists, such as operators opening and closing doors, manipulating valves, and conversing—in addition to typical plant noises. In collaboration with a nuclear power utility partner, this effort assessed the efficacy of acoustic anomaly detection when using a specific acoustic sensor that compresses data into a fixed set of features that are transferable over a standard Internet of Things communication protocol, thereby improving usability but potentially degrading detection performance. Two methods of performing automated acoustic anomaly detection were evaluated: one-class support vector machine (OC-SVM) and isolation forest (iForest). To enable the use of high-quality acoustic data encompassing both normal and anomalous conditions, the study utilized the publicly available Malfunctioning Industrial Machine Investigation and Inspection dataset, which includes real measured acoustic sensor data for a range of equipment types, model numbers, and signal-to-noise ratios (SNRs), along with a benchmark set of detection results. Using this dataset, the methods were tested and then compared against the benchmark results. The results indicated that although the specific acoustic sensor did not enable as rich a feature set extraction, the proposed methods with the limited feature set performed just as well. This provides solid justification for both the methods and the use of the proposed acoustic sensor.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Leveraging Existing Assets for Long Duration Energy Storage

Increased renewables penetration to electrical grid is necessary to reduce overall emissions from the electrical power generation sector. Nonetheless, its integration creates challenges to grid operators who must match the power being generated by intermittent renewables and other traditional energy sources with the demand from consumers, while ensuring the reliability and power quality for the entire system. Energy storage has been proposed as an alternative to natural gas peaking plants and a form to deliver excess renewable energy generation at times of peak demand. For energy storage to provide benefits to end customers (energy consumers), it must be reliable, efficient, and cost effective. The Illinois Sustainable Technology Center (ISTC), one of the surveys that integrate the Prairie Research Institute (PRI), aims to develop a Center for Energy Storage at Existing Assets (CESEA) at UIUC with the participation of Waste Pressure Corp and Ecotek Engineering USA LLC. CESEA will focus on LDES systems that can integrate to existing infrastructure in a manner that reduces the initial capital expenditure and demonstrates the ability to repurpose fossil assets that would otherwise become stranded, to serve the energy transition. CESEA aims to leverage UIUC’s unique facilities to validate LDES systems performance at a relevant operating environment. UIUC’s facilities include a 85-MW combined heat and power (CHP) power plant, two (2) solar PV plants totaling over 18 MWdc of installed capacity, an electrical grid along with a substation at transmission and distribution voltages, a 22-mile gas pipeline network operating at two pressure levels, along with steam and chilled water distribution networks. The new LDES systems will connect to the existing UIUC grid through a new test electrical station, which will have the capacity to accommodate additional connections to test new devices and technologies as part of future CESEA R&D activities. The test electrical station will contain meters, instrumentation, and controls to accurately capture data and allow optimization of control algorithms. CESEA will initially focus on technologies that: i) utilize existing equipment or facilities to perform at least one of the process steps in LDES (charging, storage, or discharging), ii) leverage mature or commercially available components or controls, iii) show potential for cost-leadership in 10+ hour storage at a commercial scale. Initial technologies that were identified to meet these criteria include Compressed Gas Energy Storage (CGES), and TES. CGES stores electricity by raising the pressure of a compressible gas inside a control volume and converting the stored energy to electricity via expansion-generation. CGES is a generalization of CAES that covers any working gas (not just air). A successful CGES demo will help to circumvent many challenges faced by CAES (long development times due to site prospecting, high cost of compression and storage, heat recovery management, etc.) by: 1) utilizing existing infrastructure (compressors, pipelines, underground storage or pressure vessels) used in the transportation and storage of industrial gases for LDES charging and storage; 2) deploying over sites already-developed for industrial applications with minor additional work; 3) leveraging the price structure of commercial industrial gas to cover the costs of electricity used during charging. A previous DOE-sponsored conceptual study (DE-FE-0032018) estimated the levelized cost of energy of a 1.1 MW / 17 MWh CGES system at $0.08/kWh, with a commercial 10x scale system cost estimated at <$0.04/kWh (Giardinella, 2022). The pilot-sized system was estimated to avoid up to 2693 tons of CO2/year.

25 ENERGY STORAGE↗

A data compression technique for synthetic aperture radar images

A data compression technique is developed for synthetic aperture radar (SAR) imagery. The technique is based on an SAR image model and is designed to preserve the local statistics in the image by an adaptive variable rate modification of block truncation coding (BTC). A data rate of approximately 1.6 bit/pixel is achieved with the technique while maintaining the image quality and cultural (pointlike) targets. The algorithm requires no large data storage and is computationally simple.

Frost, V. S.↗

Parabolized Navier-Stokes algorithm for chemically reacting flows

A second-order parabolized Navier-Stokes algorithm based on the MacCormack (1969) explicit scheme is used to study three-dimensional chemically reacting flows with finite-rate chemistry. The method can treat the chemical source term implicitly, and it accounts for the multicomponent diffusion and convection of the chemical species. The method is demonstrated with the nonreacting case of a Mach-3 flow over a double-wedge compression corner and the case of streamwise hydrogen injection at sonic velocity in a Mach-2.44 vitiated air stream.

Kamath, H.↗

Development of iterative techniques for the solution of unsteady compressible viscous flows

A research effort was initiated at Georgia Tech in February 1991 on the development of efficient techniques for the computation of 2-D and 3-D unsteady compressible flow problems. It was found that in 2-D unsteady viscous flow applications, the generalized minimal residual (GMRES) scheme was able to significantly improve the accuracy and stability characteristics of an existing 2-D ADI (Alternating Direction Implicit) time marching scheme. That is, the GMRES/ADI combination allowed 10 to 20 times larger time steps compared to an ADI scheme. Because the GMRES algorithm requires 5 to 10 times the CPU work compared to the ADI scheme, the combined GMRES/ADI scheme yields a net factor of 2 savings in CPU cost. During the past year, we also experimented with GMRES/multigrid/ADI combination. The purpose of this combination was to compute the low frequency components of the change in the flow properties from one time step to the next on a coarse grid. This strategy reduces the memory requirements of the GMRES method roughly by a factor of 4-8 for steady flow problems.

Sankar, Lakshmi N.↗

Influence of gradation on shear behavior and pore water response of sand

Here, this paper examines the influence of particle size distribution (PSD) on the shearing behavior of sand using axisymmetric triaxial compression (ATC) testing in conjunction with 3D imaging using synchrotron micro-computed tomography (SMT). Angular sand was sieved to obtain a narrow gradation (uniform) and a wide gradation (non-uniform) with uniformity coefficients (C u ) of 1.2 and 3.0, respectively. Experiments were conducted under drained conditions and a constant effective cell pressure (σ$^{'}_3$) of 50 kPa at low and high back pressures (BP). Results of paired ATC-SMT were analyzed in terms of global constitutive behavior, strain localization, and localized flow characteristics. A new particle tracking algorithm is developed to expose strain localization. Relative particle translation gradient (RPTG) results revealed that gradation affects how early the shear band develops and a tendency for narrow gradation to exhibit varying degrees of diffused shear band at high axial strain (ε 1 ) even though a clear single shear band was observed at the peak strength. Geometric tortuosity (τ) is used as a quantitative parameter to assess flow changes and the efficiency of the flow path. Representative elementary volumes (REVs) inside and outside the shear band were analyzed and the results showed a variation in flow path characteristics where wide gradation specimens had preferential flow paths.

Computed tomography↗

Compressed video camera with a moving patterned disk

A high-speed video system is disclosed that includes a moving image absorbing disk at an image plane. The disk has a pattern that passes and blocks image data. The disk is located between an event and an image sensor, or reflects an image to the image sensor. The disk is rotated at a speed that matches the desired reconstructed image frame rate. The image sensor frame data is processed using image reconstruction techniques, such as the D-AMP or TWIST algorithm, to recover a time sequence of reconstructed images. Additional images can be reconstructed for each image sensor frame if some spatial resolution is sacrificed. For continuous video, the disk speed is adjusted to the sensor frame rate. For burst mode, a single sensor image is acquired and a short image sequence is reconstructed. This image capture system works with a variety of radiations, including infrared, light, UV and X-rays.

42 ENGINEERING↗

Sparse Recovery for Scientific Data

We have built build and analyzed fundamental mathematical tools that enable sparse recovery of scientific data for high performance computing, experimental facilities and sensor measurement. The proposed work will impact many areas of research across the DOE. We have designed, developed and analyzed fast scalable algorithms for the sparse recovery of scientific data sets that may be extremely large, generated very quickly and distributed across multiple storage devices. The algorithms we developed will be used to process the copious amounts of scientific data generated by the DOE supercomputer simulations and by DOE experimental and observational facilities. They leverage the fact that while the amount of data produced can be extremely large, the actual quantities of interest (QoI's) are often sparse, either in space time, or in some feature space. Mathematically, notions of compressive sensing, including l1 regularized and total variation regularized optimization have played an important part in this effort.

97 MATHEMATICS AND COMPUTING↗

Planning and executing motions for multibody systems in free-fall

The purpose of this research is to develop an end-to-end system that can be applied to a multibody system in free-fall to analyze its possible motions, save those motions in a database, and design a controller that can execute those motions. A goal is for the process to be highly automated and involve little human intervention. Ideally, the output of the system would be data and algorithms that could be put in ROM to control the multibody system in free-fall. The research applies to more than just robots in space. It applies to any multibody system in free-fall. Mathematical techniques from nonlinear control theory were used to study the nature of the system dynamics and its possible motions. Optimization techniques were applied to plan motions. Image compression techniques were proposed to compress the precomputed motion data for storage. A linearized controller was derived to control the system while it executes preplanned trajectories.

Cameron, Jonathan M.↗