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At least 1,207 records · Page 67

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling Code Is Helping Cleveland Develop New Products

Master Builders, Inc., is a 350-person company in Cleveland, Ohio, that develops and markets specialty chemicals for the construction industry. Developing new products involves creating many potential samples and running numerous tests to characterize the samples' performance. Company engineers enlisted NASA's help to replace cumbersome physical testing with computer modeling of the samples' behavior. Since the NASA Lewis Research Center's Structures Division develops mathematical models and associated computation tools to analyze the deformation and failure of composite materials, its researchers began a two-phase effort to modify Lewis' Integrated Composite Analyzer (ICAN) software for Master Builders' use. Phase I has been completed, and Master Builders is pleased with the results. The company is now working to begin implementation of Phase II.

Source record↗

Parallelization and Algorithmic Enhancements of High Resolution IRAS Image Construction

The Infrared Astronomical Satellite caried out a nearly complete survey of the infrared sky, and the survey data are important for the study of many astrophysical phenomena. However, many data sets at other wavelengths have higher resolutions than that of the co-added IRAS maps, and high resolution IRAS images are strongly desired both for their own information content and their usefulness in correlation. The HIRES program was developed by the Infrared Processing and Analysis Center (IPAC) to produce high resolution (approx. 1') images from IRAS data using the Maximum Correlation Method (MCM). We describe the port of HIRES to the Intel Paragon, a massively parallel supercomputer, other software developments for mass production of HIRES images, and the IRAS Galaxy Atlas, a project to map the Galactic plane at 60 and 100(micro)m.

Satellite infrared IRAS IRAS maps IRAS images↗

Monitoring by Use of Clusters of Sensor-Data Vectors

The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean distance) and "sufficiently close" signifies lying at a distance less than a specified threshold value. It must be emphasized that although the IMS is intended to detect off-nominal or abnormal performance or health, it is not necessarily capable of performing a thorough or detailed diagnosis. Limited diagnostic information may be available under some circumstances. For example, the distance of a vector of incoming sensor data from the nearest cluster could serve as an indication of the severity of a malfunction. The identity of the nearest cluster may be a clue as to the identity of the malfunctioning component or subsystem. It is possible to decrease the IMS computation time by use of a combination of cluster-indexing and -retrieval methods. For example, in one method, the distances between each cluster and two or more reference vectors can be used for the purpose of indexing and retrieval. The clusters are sorted into a list according to these distance values, typically in ascending order of distance. When a set of input data arrives and is to be tested, the data are first arranged as an ordered set (that is, a vector). The distances from the input vector to the reference points are computed. The search of clusters from the list can then be limited to those clusters lying within a certain distance range from the input vector; the computation time is reduced by not searching the clusters at a greater distance.

Iverson, David L.↗

Natural Language Interface for Safety Certification of Safety-Critical Software

Model-based design and automated code generation are being used increasingly at NASA. The trend is to move beyond simulation and prototyping to actual flight code, particularly in the guidance, navigation, and control domain. However, there are substantial obstacles to more widespread adoption of code generators in such safety-critical domains. Since code generators are typically not qualified, there is no guarantee that their output is correct, and consequently the generated code still needs to be fully tested and certified. The AutoCert generator plug-in supports the certification of automatically generated code by formally verifying that the generated code is free of different safety violations, by constructing an independently verifiable certificate, and by explaining its analysis in a textual form suitable for code reviews.

Denney, Ewen↗

NOR Flash Memory Scrubbing Application for Boot File Preservation of NASA’s Descent and Landing Computer (DLC)

Progress on NASA’s Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project continues, specifically with this development of the Descent and Landing Computer (DLC). One of the DLC’s primary contributions as a SPLICE technology is its implementation of algorithms and operation of sensors to autonomously guide a spacecraft in performing more precise and safer landings on celestial bodies such as the Moon and Mars [1]. The second iteration of the DLC is known as the Engineering Test Unit (ETU) and one of its desired functionalities is the ability to preserve the fidelity of the system’s boot file through the use of memory scrubbing [2]. The ETU has two primary boards, one for housing a Multi-Processor System on a Chip (MPSoC) and the other for housing a Xilinx Kintex Ultrascale FPGA*. To emulate a memory scrubbing function implemented on the ETU’s FPGA board, the design and testing of a software application was performed on a Xilinx KCU105 FPGA evaluation board. The memory scrubbing application had to meet certain key criteria such as (1) properly utilize with the flash memory’s Serial Peripheral Interface (SPI) to read, write, and erase flash memory properly, (2) be able to detect arbitrarily large or small amounts of bit-errors, (3) be able to correct all detected errors, and (4) perform memory scrubbing indefinitely and autonomously. A prototype implementation was constructed and tested, demonstrating successful detection and correction of bit errors in multiple configurations. In the form of burst errors or singular bit flips, and in amounts of errors ranging from one to fifteen (per 256 Bytes), the application was successful in preserving memory fidelity.

Flash memory↗

A Survey of New Trends in Symbolic Execution for Software Testing and Analysis

Symbolic execution is a well-known program analysis technique which represents values of program inputs with symbolic values instead of concrete (initialized) data and executes the program by manipulating program expressions involving the symbolic values. Symbolic execution has been proposed over three decades ago but recently it has found renewed interest in the research community, due in part to the progress in decision procedures, availability of powerful computers and new algorithmic developments. We provide a survey of some of the new research trends in symbolic execution, with particular emphasis on applications to test generation and program analysis. We first describe an approach that handles complex programming constructs such as input data structures, arrays, as well as multi-threading. We follow with a discussion of abstraction techniques that can be used to limit the (possibly infinite) number of symbolic configurations that need to be analyzed for the symbolic execution of looping programs. Furthermore, we describe recent hybrid techniques that combine concrete and symbolic execution to overcome some of the inherent limitations of symbolic execution, such as handling native code or availability of decision procedures for the application domain. Finally, we give a short survey of interesting new applications, such as predictive testing, invariant inference, program repair, analysis of parallel numerical programs and differential symbolic execution.

Pasareanu, Corina S.↗

Digital bead modeling for wire-arc directed energy deposition

Prediction of 2D cross-section and full 3D geometry for stacked weld beads is critical for the outcome of wire-arc directed energy deposition (DED) parts; however, most additive path planning software packages model beads as extrusions of a rectangle. Weld beads are not rectangular, and the resulting shape is dependent upon physics effects at the moment of deposition. Physics phenomena such as the geometry of the underlying surface, the heat input of the welding mode, and the direction of gravity contribute to bead shape. Here, this paper presents a novel implicit modeling method that discretizes a 2D area or 3D volume of space into pixels or voxels and constructs fields based on these physics phenomena. The fields are combined using a weighting scheme trained on 3D scan measurements of welds and wire-arc DED prints. Pixels or voxels are added until the known amount of deposited volume has been achieved. Thereby, a strong conservation of mass principle is applied to the process. Utilizing machine learning techniques, the present model can be trained on a database of scans allowing for the representation of a wide variety of prints. Results show that this method can produce predictions with realistic bead morphology and sub-millimeter form error.

Bead geometry modeling↗

Three-dimensional computational aerodynamics in the 1980's

The future requirements for constructing codes that can be used to compute three-dimensional flows about aerodynamic shapes should be assessed in light of the constraints imposed by future computer architectures and the reality of usable algorithms that can provide practical three-dimensional simulations. On the hardware side, vector processing is inevitable in order to meet the CPU speeds required. To cope with three-dimensional geometries, massive data bases with fetch/store conflicts and transposition problems are inevitable. On the software side, codes must be prepared that: (1) can be adapted to complex geometries, (2) can (at the very least) predict the location of laminar and turbulent boundary layer separation, and (3) will converge rapidly to sufficiently accurate solutions.

Lomax, H.↗

CSM research: Testbed development

The Computational Structural Mechanics (CSM) Activity at Langley Research Center is developing methods for structural analysis on modern computers. To facilitate that research effort, a Testbed Development environment is being constructed. It is the purpose of the Testbed to insulate researchers from differences in the computer operating systems of modern computer systems and permit concentrated effort on the analytical problem rather than the analytical tools required to solve that problem. While modern computers enable the solution of larger problems of increasing complexity, they do so at a cost. Distributed computer environments, vector processing hardware and multiple processors dominate the current computer environment and threaten to overwhelm future analysis software. The systems software for current computers becomes more complex in order to manage the increasing complexity. The applications developer is caught between conflicting goals. They must take advantage of the computing power of new computer systems while maintaining a stable software development system. The CSM Testbed is being developed to address this problem for the computational structural analysis research community. The Langley CSM activity was initiated in October 1984. The current directions for the Testbed Development Team of the Langley CSM activity are discussed.

Gillian, Ronnie E.↗

Adiabatic Compression Sensitivity of Liquid Fuels and Monopropellants

Liquid rocket propellants can be sensitive to rapid compression. Such liquids may undergo decomposition and their handling may be accompanied with risk. Decomposition produces small gas bubbles in the liquid, which upon rapid compression may cause catastrophic explosions. The rapid compression can result from mechanical shocks applied on the tank containing the liquid or from rapid closure of the valves installed on the lines. It is desirable to determine the conditions that may promote explosive reactions. At Air Force Research Laboratory (AFRL), we constructed an apparatus and established a safe procedure for estimating the sensitivity of propellant materials towards mechanical shocks (Adiabatic Compression Tester). A sample is placed on a stainless steel U-tube, held isothermally at a temperature between 20 and 150 C then exposed to an abrupt mechanical shock of nitrogen gas at a pressure between 6.9 and 20.7 MPa (1000 to 3000 psi). The apparatus is computer interfaced and is driven with LABTECH NOTEBOOK-pro (registered) Software. In this presentation, the design of the apparatus is shown, the operating procedure is outlined, and the safety issues are addressed. The results obtained on different energetic materials are presented.

Ismail, Ismail M. K.↗

Next Generation Advanced Video Guidance Sensor Development and Test

The Advanced Video Guidance Sensor (AVGS) was the primary docking sensor for the Orbital Express mission. The sensor performed extremely well during the mission, and the technology has been proven on orbit in other flights too. Parts obsolescence issues prevented the construction of more AVGS units, so the next generation of sensor was designed with current parts and updated to support future programs. The Next Generation Advanced Video Guidance Sensor (NGAVGS) has been tested as a breadboard, two different brassboard units, and a prototype. The testing revealed further improvements that could be made and demonstrated capability beyond that ever demonstrated by the sensor on orbit. This paper presents some of the sensor history, parts obsolescence issues, radiation concerns, and software improvements to the NGAVGS. In addition, some of the testing and test results are presented. The NGAVGS has shown that it will meet the general requirements for any space proximity operations or docking need.

Howard, Richard T.↗

Benchmarking second and third-generation sequencing platforms for microbial metagenomics

Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq 300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics.

59 BASIC BIOLOGICAL SCIENCES↗

Research and Development Toward Massive Liquid Argon Time Projection Chambers for Neutrino Detection

Liquid argon (LAr) time projection chambers (TPC) have rapidly increased in importance as particle detectors throughout the past four decades. While much research has been completed, there are still many areas which require further development to build and operate the next generation LAr TPC experiment, such as the Deep Underground Neutrino Experiment (DUNE). These include high voltage breakdown, argon purification and purity monitoring, and vacuum ultraviolet (VUV) scintillation light measurement. Visual monitoring of high voltage breakdown is helpful in allowing assessment of the performance of high voltage component design. Thus, a system of cryogenic cameras, the first of its kind, was developed for use in a large LAr cryostat, without the need for additional electronics heating. The system functioned without problem for 50 days at cryogenic temperature, with some degradation of image quality, and provided a useful monitor for the DUNE 35-ton cryogenics systems. The system did not observe any high voltage breakdowns during the run. Further development of the concept is ongoing for future installation in other experiments. The monitoring of LAr purity using TPC data is a fundamental study for LAr TPC experiments. However, the study has not been performed for a large LAr TPC in the presence of high electronic noise. Custom software was developed and validated for the accurate reconstruction of signals in noisy TPC data. The results of the reconstruction were used to successfully measure the LAr electron lifetime with an uncertainty comparable to alternate methods of measurement. The electron lifetime of the 35-ton Phase II run is determined to be 4.12 ± 0.17 (stat.) ±0.40 (syst.) ms. For general purpose research and development of high purity LAr as a particle detection medium, a dedicated test stand was designed, constructed, and commissioned. The system is used to test the gaseous photomultiplier (GPM) performance at cryogenic temperatures. The GPM functions with photoelectron multiplication at 77 K, at a reduced gain. Further study is required to show the detector’s direct sensitivity to LAr VUV scintillation light.

Thiesse, Matthew↗

THE THEORETICAL ASTROPHYSICAL OBSERVATORY: CLOUD-BASED MOCK GALAXY CATALOGS

We introduce the Theoretical Astrophysical Observatory (TAO), an online virtual laboratory that houses mock observations of galaxy survey data. Such mocks have become an integral part of the modern analysis pipeline. However, building them requires expert knowledge of galaxy modeling and simulation techniques, significant investment in software development, and access to high performance computing. These requirements make it difficult for a small research team or individual to quickly build a mock catalog suited to their needs. To address this TAO offers access to multiple cosmological simulations and semi-analytic galaxy formation models from an intuitive and clean web interface. Results can be funnelled through science modules and sent to a dedicated supercomputer for further processing and manipulation. These modules include the ability to (1) construct custom observer light cones from the simulation data cubes; (2) generate the stellar emission from star formation histories, apply dust extinction, and compute absolute and/or apparent magnitudes; and (3) produce mock images of the sky. All of TAO’s features can be accessed without any programming requirements. The modular nature of TAO opens it up for further expansion in the future.

79 ASTRONOMY AND ASTROPHYSICS↗

High-Accuracy Heats of Formation for Alkane Oxidation: From Small to Large via the Automated CBH-ANL Method

It is generally challenging to obtain high-accuracy predictions for the heat of formation for species with more than a handful of heavy atoms, such as those of importance in standard combustion mechanisms. To this end, we construct the CBH-ANL approach and illustrate that, for a set of 194 alkane oxidation species, it can be used to produce ΔH f (o K) values with 2σ uncertainties of 0.2-0.5 kcal mol -1 . This set includes the alkanes, hydroperoxides, and alkyl, peroxy, and hydroperoxyalkyl radicals for 17 representative hydrocarbon fuels containing up to 10 heavy atoms with various degrees of branching in the alkane backbone. The CBH-ANL approach, automated in the QTC and AutoMech software suites, builds balanced chemical equations for the calculation of ΔH f (o K), in which the reference species may be up to five heavy atoms. The high-level ANLo and ANL1 reference ΔH f (o K) values are further refined for even the largest of these reference species with a novel laddering approach. We perform a comprehensive quantification of the uncertainties for both the individual reference species (the largest of which is 0.15 kcal mol -1 ) and the propagation of those uncertainties when used in the calculation of ΔH f (o K) for the 194 target species. Here we examine the sensitivity of the predicted ΔH f (o K) values to (i) electronic energies from various methods, including ωB97X-D/cc-pVTZ, B2PLYP-D3/cc-pVTZ, CCSD(T)-F12b/cc-pVDZ-F12//B2PLYP-D3/cc-pVTZ, and CCSD(T)-F12b/cc-pVTZ-F12//B2PLYP-D3/cc-pVTZ; (ii) the zero-point vibrational energies (ZPVEs), where we consider harmonic ZPVEs as well as two scaling-based estimates of the anharmonic ZPVEs, all implemented for both ωB97X-D/cc-pVTZ and B2PLYP-D3/cc-pVTZ calculations; (iii) the particular CBH-ANL scheme employed; and (iv) the procedure for choosing the reference conformer for the analyses. The discussion concludes with a summary of the estimated overall uncertainty in the predictions and a validation of the predictions for the alkane subset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parallel general purpose multiobjective optimization framework with application to electron beam dynamics

Particle accelerators are invaluable tools for research in the basic and applied sciences, such as materials science, chemistry, the biosciences, particle physics, nuclear physics and medicine. The design, commissioning, and operation of accelerator facilities is a nontrivial task, due to the large number of control parameters and the complex interplay of several conflicting design goals. The Argonne Wakefield Accelerator facility has some unique challenges resulting from its purpose to carry out advanced accelerator R&D. Individual experiments often have challenging beam requirements, and the physical configuration of the beam lines is often changed to accommodate the variety of supported experiments. The need for rapid deployment of different operational settings further complicates the optimization work that must be done for multiple constraints and challenging operational regimes. One example of this is an independently staged two-beam acceleration experiment which requires the construction of an additional beam line (this is now in progress). The high charge drive beam, well into the space charge regime, must be threaded through small aperture (17.6 mm) decelerating structures. In addition, the bunch length must be sufficiently short to maximize power generation in the decelerator. We propose to tackle this problem by means of multiobjective optimization algorithms which also facilitate a parallel deployment. In order to compute solutions in a meaningful time frame, a fast and scalable software framework is required. In this paper, we present a general-purpose framework for simulation-based multiobjective optimization methods that allows the automatic investigation of optimal sets of machine parameters. Using evolutionary algorithms as the optimizer and opal as the forward solver, validation experiments and results of multiobjective optimization problems in the domain of beam dynamics are presented. Optimized solutions for the new high charge drive beam line found by the framework were used to finish the design of a two beam acceleration experiment. The selected solution along with the associated beam parameters is presented.

43 PARTICLE ACCELERATORS↗

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 3: Wiring diagrams

The Midas System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in Phase I of the overall program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 2 x 100,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. The MIDAS construction and wiring diagrams are given.

Kriegler, F. J.↗