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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Metabolic flux optimization of iterative pathways through orthogonal gene expression control: Application to the β-oxidation reversal

Balancing relative expression of pathway genes to minimize flux bottlenecks and metabolic burden is one of the key challenges in metabolic engineering. This is especially relevant for iterative pathways, such as reverse β-oxidation (rBOX) pathway, which require control of flux partition at multiple nodes to achieve efficient synthesis of target products. Here, we develop a plasmid-based inducible system for orthogonal control of gene expression (referred to as the TriO system) and demonstrate its utility in the rBOX pathway. Leveraging effortless construction of TriO vectors in a plug-and-play manner, we simultaneously explored the solution space for enzyme choice and relative expression levels. Remarkably, varying individual expression levels led to substantial change in product specificity ranging from no production to optimal performance of about 90% of the theoretical yield of the desired products. We obtained titers of 6.3 g/L butyrate, 2.2 g/L butanol and 4.0 g/L hexanoate from glycerol in E. coli, which exceed the best titers previously reported using equivalent enzyme combinations. Since a similar system behavior was observed with alternative termination routes and higher-order iterations, we envision our approach to be broadly applicable to other iterative pathways besides the rBOX. Here, considering that high throughput, automated strain construction using combinatorial promoter and RBS libraries remain out of reach for many researchers, especially in academia, tools like the TriO system could democratize the testing and evaluation of pathway designs by reducing cost, time and infrastructure requirements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Autonomous Electrochemistry Platform with Real-Time Normality Testing of Voltammetry Measurements Using ML

Electrochemistry workflows utilize various instruments and computing systems to execute workflows consisting of electrocatalyst synthesis, testing and evaluation tasks. The heterogeneity of the software and hardware of these ecosystems makes it challenging to orchestrate a complete workflow from production to characterization by automating its tasks. We propose an autonomous electrochemistry computing platform for a multi-site ecosystem that provides the services for remote experiment steering, real-time measurement transfer, and AI/ML-driven analytics. We describe the integration of a mobile robot and synthesis workstation into the ecosystem by developing custom hub-networks and software modules to support remote operations over the ecosystem’s wireless and wired networks. We describe a workflow task for generating I-V voltammetry measurements using a potentiostat, and a machine learning framework to ensure their normality by detecting abnormal conditions such as disconnected electrodes. We study a number of machine learning methods for the underlying detection problem, including smooth, non-smooth, structural and statistical methods, and their fusers. We present experimental results to illustrate the effectiveness of this platform, and also validate the proposed ML method by deriving its rigorous generalization equations.

Alnajjar, Anees↗
DOE OSTI2013

Cyber/Physical Security Vulnerability Assessment Integration

Securing high value and critical assets is one of the biggest challenges facing this nation and others around the world. In modern integrated systems, there are four potential modes of attack available to an adversary: • physical only attack, • cyber only attack, • physical-enabled cyber attack, • cyber-enabled physical attack. Blended attacks involve an adversary working in one domain to reduce system effectiveness in another domain. This enables the attacker to penetrate further into the overall layered defenses. Existing vulnerability assessment (VA) processes and software tools which predict facility vulnerabilities typically evaluate the physical and cyber domains separately. Vulnerabilities which result from the integration of cyber-physical control systems are not well characterized and are often overlooked by existing assessment approaches. In this paper, we modified modification of the timely detection methodology, used for decades in physical security VAs, to include cyber components. The Physical and Cyber Risk Analysis Tool (PACRAT) prototype illustrates an integrated vulnerability assessment that includes cyber-physical interdependencies. Information about facility layout, network topology, and emplaced safeguards is used to evaluate how well suited a facility is to detect, delay, and respond to attacks, to identify the pathways most vulnerable to attack, and to evaluate how often safeguards are compromised for a given threat or adversary type. We have tested the PACRAT prototype on critical infrastructure facilities and the results are promising. Future work includes extending the model to prescribe the recommended security improvements via an automated cost-benefit analysis.

MacDonald, Douglas G.↗
DOE OSTI2019

Convex Relaxations of the Network Flow Problem Under Cycle Constraints

In this paper, we consider the problem of optimizing the flows in a lossless flow network with additional nonconvex cycle constraints on nodal variables; such constraints appear in several applications, including electric power, water distribution, and natural gas networks. This problem is a nonconvex version of the minimum-cost network flow problem (NFP), and to solve it, we propose three different approaches. One approach is based on solving a convex approximation of the problem, obtained by augmenting the cost function with an entropy-like term to relax the nonconvex constraints. We show that the approximation error, for which we give an upper bound, can be made small enough for practical use. An alternative approach is to solve the classical NFP, that is, without the cycle constraints, and solve a separate optimization problem afterwards in order to recover the actual flows satisfying the cycle constraints; the solution of this separate problem maximizes the individual entropies of the cycles. The third approach is based on replacing the nonconvex constraint set with a convex inner approximation, which yields a suboptimal solution for the cyclic networks with each edge belonging to at most two cycles. We validate the practical usefulness of the theoretical results through numerical examples, in which we study the standard test systems for water and electric power distribution networks.

42 ENGINEERING↗
DOE OSTI2019

Large $N_c$ Thermodynamics with Dynamical Fermions

We present a progress report on our investigation of the thermodynamics of QCD with $N_f=2$ flavors of dynamical Wilson fermions in the limit of a large number of colors $N_c$. To date, studies of the thermodynamics of QCD at large $N_c$ have been limited to the quenched approximation, i.e., to the behavior of pure $\mathrm{SU}(N_c)$ gauge theory at large $N_c$. This is the first study of thermodynamics at large $N_c$ using dynamical fermions, and thus the first study able to test whether the quenched approximation is a valid way to investigate large $N_c$ thermodynamics. After reviewing 't Hooft's large $N_c$ limit, we discuss the automation we use to make this study feasible, and finally compare our preliminary physics results for $\mathrm{SU}(3-5)$ with large $N_c$ expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Portable Waveguide-Based Optical Biosensor

Rapid, on-site diagnostics allow for timely intervention and response for warfighter support, environmental monitoring, and global health needs. Portable optical biosensors are being widely pursued as a means of achieving fieldable biosensing due to the potential speed and accuracy of optical detection. We recently developed the portable engineered analytic sensor with automated sampling (PEGASUS) with the goal of developing a fieldable, generalizable biosensing platform. Here, we detail the development of PEGASUS’s sensing hardware and use a test-bed system of identical sensing hardware and software to demonstrate detection of a fluorescent conjugate at 1 nM through biotin-streptavidin chemistry.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Evaluations of Silicon Carbide Temperature Monitors

The effect of irradiation on materials properties is an important field of study for materials usage in both fission and fusion systems for energy production. Neutron flux and energy spectrums are well understood; however, the irradiation temperature can be more difficult to determine. Since the early 1960s, Silicon Carbide (SiC) has been used as a passive post-irradiation temperature monitor because the irradiation defects anneal out above the irradiation temperature. Irradiation temperature is determined by measuring a property change after isochronal annealing or during a continuously monitored annealing process. There are many properties that may be measured including electrical resistivity, bulk density, dimensions, thermal diffusivity, or lattice spacing. Electrical resistivity is accepted as a robust measurement technique; however, such method is time-consuming since the steps involved must be performed in a serial manner. The use of thermal expansion from continuous dilatometry is an automated process requiring minimal setup time. As part of a Nuclear Science User Facilities (NSUF) project, low dose silicon carbide monitors were irradiated in the BR2 material test reactor at SCK, Belgium, and were then evaluated at the Idaho National Laboratory (INL) High Temperature Test Laboratory (HTTL) to determine their peak temperature achieved during irradiation. The technical significance of this work was that the monitors were irradiated to a dose that was significantly less than recommended in published literature. This paper will discuss the evaluation processes available at HTTL and the performance of the low dose silicon carbide temperature monitors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Robust Localization of an Arbitrary Distribution of Radioactive Sources for Aerial Inspection - 18094

Radiation source detection has seen various applications in the past decade, ranging from the detection of dirty bombs in public places to scanning critical nuclear facilities for leakage or flaws, and in the autonomous inspection of nuclear sites. Despite the success in detecting single point sources, or a small number of spatially separated point sources, most of the existing algorithms fail to localize sources in complex scenarios with a large number of point sources or non-trivial distributions and bulk sources. Even in simpler environments, most existing algorithms are not scalable to larger regions and/or higher dimensional spaces. For effective autonomous inspection, we not only need to estimate the positions of the sources, but also the number, distribution and intensities of each of them. In this paper, we present a novel algorithm for the robust localization of an arbitrary distribution of radiation sources using multi-layer sequential Monte Carlo methods coupled with suitable clustering algorithms. We achieve near-perfect accuracy, in terms of F1-scores (> 0.95), while allowing the algorithm to scale, both to large regions in space, and to higher dimensional spaces (5 tested). (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

RE-INTEGRATE EMT Simulation Tool: Input Data Processing Layer for Bulk Power System

This paper introduces an advanced input data processing layer for EMT simulations of large-scale bulk power systems. The paper proposes two versions of the RE-INTEGRATE EMT simulation tool, RE-INTEGRATE Gen-0 and RE-INTEGRATE Gen-1, which are developed to enhance simulation generalizability, scalability, and accuracy. The framework leverages a generic class design for components to incorporate linear equations, which are generated by discretizing the Differential-Algebraic Equations (DAEs) that represent the dynamics of the components. In addition, the framework employs a parsing algorithm that parses a power system’s raw and dyr files to generate a connectivity graph which is then traversed to form the overall system’s dynamics. The proposed input data processing layer is used to simulate the IEEE 39-bus test system. The obtained results demonstrate the framework’s capability to achieve simulation scalability and accuracy. Further, the results indicate that EMT simulations performed using the proposed automations can effectively handle complex grid configurations.

Mishra, Rahul [ORNL] (ORCID:0000000328205932)↗
DOE OSTI2022

Automated Production of Optimization-Based Control Logics for Dynamic Facade Systems, with Experimental Application to Two-Zone External Venetian Blinds

The primary goal of this research is to devise a system that produces controllers for complex fenestration systems that perform nearly as well as Model Predictive Control but at a level of cost and implementation complexity that rivals simple heuristic controls. To this end, a cloud-based automated controller production system has been set up for a motorized external Venetian blind device, with a simple web interface that can be used by non-experts. The computation cost per controller is in the range of a few dollars, and the control logic is simple enough to be implemented on small and cheap distributed controllers. The web interface allows the user to specify some details of their particular building and window configuration, including orientation, latitude, interior geometries, and lighting and HVAC system parameters. Upon submittal, a cloud-based system configures the necessary files and commands, and then runs thousands of optimizations with them. Once the calculations are finished, the system produces a lookup table and interpolation-based controller scripts that can be used on a simple and cheap distributed controller. This paper describes the underlying models and optimization processes. It also describes the resulting control logics for two cases tested at Lawrence Berkeley National Laboratory’s Advanced Windows Testbed Facility: illuminance maximization subject to glare constraints; and lighting + HVAC energy minimization. The performance of the model-based controllers produced by the automated web-based system are compared to a heuristic ‘block beam’ controller in physical experiments at the Testbed. The experimental results are supplemented by simulation experiments with the same configuration as the Testbed. The results show the illuminance maximizing controller significantly outperforms the heuristic controller in terms of glare avoidance, and also outperforms it in terms of hours of daylight autonomy. The energy minimizing controller also outperforms the heuristic controller. This paper also discusses how the web-based system may be extended to consider other configurations, such as electrochromic windows and thermally massive HVAC systems. Potential roles for this type of system within the building design and construction industry are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY202 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗
DOE OSTI2020

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY2020 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time-separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗
DOE OSTI2017

Improved performance comparisons of radioxenon systems for low level releases in nuclear explosion monitoring

The Comprehensive Nuclear-Test-Ban Treaty bans all nuclear tests and mandates development of verification measures to detect treaty violations. One verification measure is detection of radioactive xenon isotopes produced in the fission of actinides. The International Monitoring System (IMS) currently deploys automated radioxenon systems that can detect four radioxenon isotopes. Radioxenon systems with lower detection limits are currently in development. Historically, the sensitivity of radioxenon systems was measured by the minimum detectable concentration for each isotope. In this paper we analyze the response of radioxenon systems using rigorous metrics in conjunction with hypothetical representative releases indicative of an underground nuclear explosion instead of using only minimum detectable concentrations. Our analyses incorporate the impact of potential spectral interferences on detection limits and the importance of measuring isotopic ratios of the relevant radioxenon isotopes in order to improve discrimination from background sources particularly for low-level releases. To provide a sufficient data set for analysis, hypothetical representative releases are simulated every day from the same location for an entire year. The performance of three types of samplers are evaluated assuming they are located at 15 IMS radionuclide stations in the region of the release point. The performance of two IMS-deployed samplers and a next-generation system is compared with proposed metrics for detection and discrimination using representative releases from the nuclear test site used by the Democratic People’s Republic of Korea.

Haas, Derek A.↗
DOE OSTI2013

Validity of automated x-ray photoelectron spectroscopy algorithm to determine the amount of substance and the depth distribution of atoms

The author reports a systematic study of the range of validity of a previously developed algorithm for automated x-ray photoelectron spectroscopy analysis, which takes into account the variation in both peak intensity and the intensity in the background of inelastically scattered electrons. This test was done by first simulating spectra for the Au4d peak with gold atoms distributed in the form of a wide range of nanostructures, which includes overlayers with varying thickness, a 5 A layer of atoms buried at varying depths and a substrate covered with an overlayer of varying thickness. Next, the algorithm was applied to analyze these spectra. The algorithm determines the number of atoms within the outermost 3 {lambda} of the surface. This amount of substance is denoted AOS{sub 3{lambda}} (where {lambda} is the electron inelastic mean free path). In general the determined AOS{sub 3{lambda}} is found to be accurate to within {approx}10-20% depending on the depth distribution of the atoms. The algorithm also determines a characteristic length L, which was found to give unambiguous information on the depth distribution of the atoms for practically all studied cases. A set of rules for this parameter, which relates the value of L to the depths where the atoms are distributed, was tested, and these rules were found to be generally valid with only a few exceptions. The results were found to be rather independent of the spectral energy range (from 20 to 40 eV below the peak energy) used in the analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators

We present an adaptive grid matrix-free operator approximation scheme based on a "product-convolution" interpolation of convolution operators. This scheme is appropriate for operators that are locally translation-invariant, even if these operators are high rank or full rank. Such operators arise in Schur complement methods for solving partial differential equations (PDEs), as Hessians in PDE-constrained optimization and inverse problems, as integral operators, as covariance operators, and as Dirichlet-to-Neumann maps. Constructing the approximation requires computing the impulse responses of the operator to point sources centered on nodes in an adaptively refined grid of sample points. A randomized a posteriori error estimator drives the adaptivity. Once constructed, the approximation can be efficiently applied to vectors using the fast Fourier transform. The approximation can be efficiently converted to hierarchical matrix (H-matrix) format, then inverted or factorized using scalable H-matrix arithmetic. The quality of the approximation degrades gracefully as fewer sample points are used, allowing cheap lower quality approximations to be used as preconditioners. Furthermore, this yields an automated method to construct preconditioners for locally translation-invariant Schur complements. We directly address issues related to boundaries and prove that our scheme eliminates boundary artifacts. We test the scheme on a spatially varying blurring kernel, on the nonlocal component of an interface Schur complement for the Poisson operator, and on the data misfit Hessian for an advection dominated advection-diffusion inverse problem. Numerical results show that the scheme outperforms existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Microfluidic-Based sample chips for radioactive solutions

Historical nuclear fuel cycle process sampling techniques required sample volumes ranging in the tens of milliliters. The radiation levels experienced by analytical personnel and equipment, in addition to the waste volumes generated from analysis of these samples, have been significant. These sample volumes also impacted accountability inventories of required analytes during process operations. To mitigate radiation dose and other issues associated with the historically larger sample volumes, a microcapillary sample chip was chosen for further investigation. The ability to obtain microliter volume samples coupled with a remote automated means of sample loading, tracking, and transporting to the analytical instrument would greatly improve analytical efficiency while reducing both personnel exposure and radioactive waste volumes. Sample chip testing was completed to determine the accuracy, repeatability, and issues associated with the use of microfluidic sample chips used to supply µL sample volumes of lanthanide analytes dissolved in nitric acid for introduction to an analytical instrument for elemental analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Polarized 3He Gas Circulating Technologies for Neutron Analyzers

We describe the development of an integrated system for quasi-continuous operation of a large volume neutron analyzer. The system consists of a non-magnetic diaphragm compressor, a prototype large volume helium polarizer, a surrogate neutron analyzer, a non-depolarizing gas storage reservoir, a non-ferrous valve manifold for handling gas distribution, a custom rubidium-vapor gas return purifier, and wire-wound transfer lines, all of which are immersed in a two-meter external magnetic field. Over the Phase II period we focused on three major tasks required for the successful deployment of these types of systems: 1) design and implementation of gas handling hardware, 2) automation for long-term operation, and 3) improvements in polarizer performance, specifically fabrication of aluminosilicate optical pumping cells. In this report we describe the design, implementation, and testing of the gas handling hardware. We describe improved polarizer performance resulting from improved cell materials and fabrication methods. These improvements yielded valved 8.5 liter cells with relaxation times greater than 12 hours. Pumping this cell with 1500W laser power with 1.25nm linewidth yielded peak polarizations of 60%, measured both inside and outside the polarizer. Fully narrowing this laser to 0.25nm, demonstrated separately on one stack of the four, would have allowed 70% polarization with this cell. We demonstrated the removal of 5 liters of polarized helium from the polarizer with no measured loss of polarization. We circulated the gas through a titanium-clad compressor with polarization loss below 3% per pass. We also prepared for the next phase of development by refining the design of the polarizer so that it can be engineer-certified for pressurized operation. The performance of our system far exceeds comparable efforts elsewhere.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗