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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

QM/MM Simulation (B3LYP) of the RNase A Cleavage-Transesterification Reaction Supports a Triester AN+DN Associative Mechanism with an O2´ H Internal Proton Transfer

The mechanism of the backbone cleavage transesterification step of the RNase A enzyme remains controversial even after 60 years of study. We report QM/MM free energy calculations for two optimized reaction paths based on an analysis of all structural data and identified by a search for reaction coordinates using a reliable quantum chemistry method (B3LYP), equilibrated structural optimizations, and free energy estimations. Both paths are initiated by nucleophilic attack of the ribose O2? oxygen on the neighboring diester phosphate bond and both reach the same product state (PS) (a O3??O2? cyclic phosphate and a O5? hydroxyl terminated fragment). Path 1, resembles the widely accepted dianionic transition state (TS) general acid (His 119)/base (His 12) classical mechanism. However, this path has a barrier (25 kcal/mol) higher than that of the rate limiting hydrolysis step and a very loose TS. In Path 2, the proton initially coordinating the O2? migrates to the non-bridging O1P in the initial reaction path rather than directly to the general base resulting in a triester (substrate as base) AN+DN mechanism with a monoanionic weakly stable intermediate. The structures in the transition region are associative with low barriers (TS1 10, TS2 7.5 kcal/mol). The Path 2 mechanism is consistent with the many results from enzyme and buffer catalyzed and uncatalyzed analog reactions and leads to a PS consistent with the reactive state for the following hydrolysis step. The differences between the consistently estimated barriers in Path 1 and 2 lead to a 1011 difference in rate strongly supporting the less accepted triester mechanism.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2025

A co-registered in-situ and ex-situ dataset from wire arc additive manufacturing process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data-centric approach emphasizes leveraging sensor data available throughout the production process to optimize performance. Integration of extensive data analysis provides opportunities for improving precision, reducing waste, and enhancing the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes a comprehensive description of the deposition process, process parameters, welding characteristics and acoustic data collected in-situ, and X-Ray Computed Tomography data of the build.

42 ENGINEERING↗
DOE OSTI2015

Analysis of the scintillation mechanism in a pressurized {sup 4}He fast neutron detector using pulse shape fitting

An empirical investigation of the scintillation mechanism in a pressurized {sup 4}He gas fast neutron detector was conducted using pulse shape fitting. Scintillation signals from neutron interactions were measured and averaged to produce a single generic neutron pulse shape from both a {sup 252}Cf spontaneous fission source and a (d,d) neutron generator. An expression for light output over time was then developed by treating the decay of helium excited states in the same manner as the decay of radioactive isotopes. This pulse shape expression was fitted to the measured neutron pulse shape using a least-squares optimization algorithm, allowing an empirical analysis of the mechanism of scintillation inside the {sup 4}He detector. A further understanding of this mechanism in the {sup 4}He detector will advance the use of this system as a neutron spectrometer. For {sup 252}Cf neutrons, the triplet and singlet time constants were found to be 970 ns and 686 ns, respectively. For neutrons from the (d,d) generator, the time constants were found to be 884 ns and 636 ns. Differences were noted in the magnitude of these parameters compared to previously published data, however the general relationships were noted to be the same and checked with expected trends from theory. Of the excited helium states produced from a {sup 252}Cf neutron interaction, 76% were found to be born as triplet states, similar to the result from the neutron generator of 71%. The two sources yielded similar pulse shapes despite having very different neutron energy spectra, validating the robustness of the fits across various neutron energies.

36 MATERIALS SCIENCE↗
DOE OSTI2013

DynaM: Dynamic Multiresolution Data Representation for Large-Scale Scientific Analysis

Fast growing large-scale systems enable scientific applications to run at a much larger scale and accordingly produce gigantic volumes of simulation output. Such data imposes a grand challenge to post-processing tasks such as visualization and data analysis, because these tasks are often performed at a host machine that is remotely located and equipped with much less memory and storage resources. During the simulation runs, it is also desirable for scientists to be able to interactively monitor and steer the progress of simulation. This requires scientific data to be represented in an efficient form for initial exploration and computation steering. In this paper, we propose DynaM a software framework that can represent scientific data in a multiresolution form, and dynamically organize data blocks into an optimized layout for efficient scientific analysis. DynaM supports a convolution-based multiresolution data representation for abstracting scientific data for visualization at a wide spectrum of resolution. To support the efficient generation and retrieval of different data granularities from such representation, a dynamic data organization in DynaM is enabled to cater distinct peculiarities of different size data blocks for efficient and balanced I/O performance. Our experimental results demonstrate that DynaM can efficiently represent large scientific dataset and speed up the visualization of multidimensional scientific data. An up to 29 times speedup is achieved on Jaguar supercomputer at Oak Ridge National Laboratory.

Tian, Yuan↗
DOE OSTI2023

Sensitivity-Driven Experimental Design to Facilitate Control of Dynamical Systems

Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high-fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. Here this article proposes an optimization-centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA’s X-43 hypersonic flight tests.

42 ENGINEERING↗
DOE OSTI2023

Principal Component Analysis of azimuthal flow in intermediate-energy heavy-ion reactions

Principal Component Analysis (PCA) via Singular Value Decomposition (SVD) of large datasets is an adaptive exploratory method to uncover natural patterns underlying the data. Several recent applications of the PCA-SVD to event-by-event single-particle azimuthal angle distribution matrices in ultra-relativistic heavy-ion collisions at RHIC-LHC energies indicate that the sine and cosine functions chosen a priori in the traditional Fourier analysis are naturally the most optimal basis for azimuthal flow studies according to the data itself. We perform PCA-SVD analyses of mid-central Au+Au collisions at $E$ $beam$ / $A$ =1.23 GeV simulated using an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model to address the following two questions: (1) if the principal components of the covariance matrix of nucleon azimuthal angle distributions in heavy-ion reactions around 1 GeV/nucleon are naturally sine and/or cosine functions and (2) what if any advantages the PCA-SVD may have over the traditional flow analysis using the Fourier expansion for studying the EOS of dense nuclear matter. In conclusion, we find that (1) in none of our analyses the principal components come out naturally as sine and/or cosine functions, (2) while both the eigenvectors and eigenvalues of the covariance matrix are appreciably EOS dependent, the PCA-SVD has no apparent advantage over the traditional Fourier analysis for studying the EOS of dense nuclear matter using the azimuthal collective flow in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Domain Decomposition for Integer Optimal Control with Total Variation Regularization

Total variation integer optimal control problems admit solutions and necessary optimality conditions via geometric variational analysis. In spite of the existence of said solutions, algorithms which solve the discretized objective suffer from high numerical cost associated with the combinatorial nature of integer programming. Hence, such methods are often limited to small and medium-sized problems. We propose a globally convergent, coordinate descent–inspired algorithm that allows tractable subproblem solutions restricted to a partition of the domain. Our decomposition method solves relatively small trust-region subproblems that modify the control variable on a subdomain only. Given nontrivial subdomain overlap, we prove that a global first-order necessary optimality condition is equivalent to a first-order necessary optimality condition per subdomain. We additionally show that a sufficient decrease is achieved on a single subdomain by way of a trust-region subproblem solver using geometric measure–theoretic arguments, which we integrate with a greedy patch selection to prove convergence of our algorithm. In conclusion, we demonstrate the practicality of our algorithm on a benchmark large-scale, PDE-constrained integer optimal control problem and find that our method is faster than the state of the art.

domain decomposition↗
DOE OSTI2021

Potential benefits and optimization of cool-coated office buildings: A case study in Chongqing, China

Increasing envelope facet albedos considerably reduces solar heat gain, thus yielding building cooling energy savings. Few studies have explored the potential benefits of utilizing cool coatings on building envelopes (“cool-coated buildings”) based on life-cycle cost analysis. A holistic approach integrating the field testing, building energy simulation, and a 20-year life-cycle-based optimization was developed to explore cool-coated building performance and the maximum net savings of optimal building envelope retrofit and design. Experimental results showed that applying cool coatings to a west wall of an office building in Chongqing, China reduced its exterior surface temperature by up to 9.3 °C in summer. Additionally, simulation results showed that in Chongqing, making the roof and walls cool could reduce annual HVAC electricity use by up to 11.9% in old buildings (with poorly insulated envelopes) and up to 5.9% in new buildings. Retrofitting old buildings with a cool roof provided the net savings per modified area with present values up to 42.8 CNY/m2; retrofitting a new building with a cool roof or cool walls was not cost-effective. Optimizing both envelope insulation and envelope albedo can achieve 5.6 times the net savings of optimizing the insulation only, and 1.6 times that of optimizing albedo only.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Gating System Design Optimization for Investment Casting Process

This article aims to optimize specific castings, characterized as an element of the continuous track for armored vehicle. During the primary melts, defects in the form of oxide films and shrinkage porosity occurred. Steel 20ChGSNM described by the Russian GOST standard was used as a batch material, and the investment casting method was selected for production. To eliminate the above-mentioned defects, only changes in the gating system were allowed, because the interference with an ongoing production regarding technical and technological parameters was unacceptable by the manufacturer. Numerical simulation, x-ray, macro-structural and micro-structural analysis were used during the optimization process. The three variants were analyzed, and the achieved results demonstrated that it is possible to significantly affect the casting internal homogeneity by modifying the gating system individual parts. The final variant ensured a decrease in defects by up to 90% and the production of casting having the quality required by the customer.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-T-529: Is MFO-IMPT Robust Enough for the Treatment of Head and Neck Tumors? A 2-Year Outcome Analysis Following Proton Therapy On the First 50 Oropharynx Patients at the MD Anderson Cancer Center

Purpose: Multi-field optimization intensity modulated proton therapy (MFO-IMPT) for oropharyngeal tumors has been established using robust planning, robust analysis, and robust optimization techniques. While there are inherent uncertainties in proton therapy treatment planning and delivery, outcome reporting are important to validate the proton treatment process. The purpose of this study is to report the first 50 oropharyngeal tumor patients treated de-novo at a single institution with MFO-IMPT. Methods: The data from the first 50 patients with squamous cell carcinoma of the oropharynx treated at MD Anderson Cancer Center from January 2011 to December 2014 on a prospective IRB approved protocol were analyzed. Outcomes were analyzed to include local, regional, and distant treatment failures. Acute and late toxicities were analyzed by CTCAE v4.0. Results: All patients were treated with definitive intent. The median follow-up time of the 50 patients was 25 months. Patients by gender were male (84%) and female (16%). The average age was 61 years. 50% of patients were never smokers and 4% were current smokers. Presentation by stage; I–1, II–0, III– 9, IVA–37 (74%), IVB–3. 88% of patients were HPV/p16+. Patients were treated to 66–70 CGE. One local failure was reported at 13 months following treatment. One neck failure was reported at 12 months. 94% of patients were alive with no evidence of disease. One patient died without evidence of disease. There were no Grade 4 or Grade 5 toxicities. Conclusion: MFO-IMPT for oropharyngeal tumors is robust and provides excellent outcomes 2 years after treatment. A randomized trial is underway to determine if proton therapy will reduce chronic late toxicities of IMRT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Design for Carbon Conversion Product Pathways with Nuclear Power Plant Integration (PCC)

Coal is a globally abundant resource that historically has been used for power generation via combustion. As the power industry replaces coal with cleaner methods of generation, energy rich coal could be used in other chemical and fuel applications. This study presents a coal utilization option in which coal combustion is replaced with a carbon-free nuclear power plant and the coal is upgraded to valuable products for a variety of markets. Coal is prepared for conversion first by the pyrolysis process, which will optimize solid, liquid, and gaseous products based on the market size and potential product value, maximizing the monetary value of coal. This process is designed using bituminous coal from the Appalachian region as a basis to provide a pathway to preserve or transition coal-related jobs and create new jobs associated with the clean energy transition. Process modeling will be used to determine each component’s sensitivities, costs, inputs, and outputs Advanced and light-water reactors are considerations to supply the heat, steam, and electricity to the process. This paper focuses on the technical and market analysis used to determine the optimal processes and product pathways for the carbon refinery. Product pathways are on activated carbon, formic acid synthesis, and methanol synthesis for further upgrading to marketable chemical and polymer products.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Quantifying and Qualifying Alloys Based on Level of Homogenization: A U-10Mo Alloy Case Study

Homogenization heat treatment is performed to attain uniformity in microstructure which is helpful to achieve the desired workability and microstructure in final products and, eventually, to gain predictive and consistent performance. Fabrication of low-enriched uranium alloys with 10 wt% molybdenum (U-10Mo) fuel plates involves multiple thermomechanical processing steps. It is well known that the molybdenum homogeneity in the final formed product affects the performance in the nuclear reactor. Here, to ensure uniform homogenization, a statistical method is proposed to quantify and characterize the molybdenum concentration variation in U-10Mo fuel plates by analyzing the molybdenum concentration measurement data from scanning electron microscopy energy dispersive spectroscopy line-scan. Statistical tolerance intervals (TI) are employed to determine the qualification of the U-10Mo fuel plate. We formulate an argument for the minimum number of independent samples to define fuel plate qualification if no molybdenum measurement data are available in advance and demonstrate that the given TI requirements can be equivalently reduced to a sample variance criterion in this application. The outcome of the statistical analysis can be used to optimize casting design and eventually increase productivity and reduce fabrication costs. The statistical strategy developed in this paper can be implemented for other applications especially in the field of material manufacturing to assess qualification requirements and monitor and improve the process design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

STOCHASTIC OPTIMIZATION FOR LONG TERM CAPITAL STRUCTURES, SYSTEMS, AND COMPONENTS REFURBISHMENT AND REPLACEMENT

As commercial nuclear power plants (NPPs) pursue extended plant operations in the form of Second License Renewals (SLRs), opportunities exist for these plants to provide capital investments to ensure long-term, safe, and economic performance. Several utilities have already announced their intention to pursue extended operations for one or more of their NPPs via SLR2. The goal of this research is to develop a riskinformed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions in NPP operations. In order to prioritize project selection via a riskinformed approach we developed a single decision-making tool that integrates safety/reliability, cost, and stochastic optimization models to provide users with data analysis capabilities to more cost effectively manage plant assets. Both stochastic analysis methods—such as Monte Carlo-based sampling strategies—and multi-stage stochastic optimization strategies are employed to provide priority lists to decisionmakers in support of risk-informed decisions. We applied the proposed method to a trial application of projected replacement/refurbishment expenditures for plant capital assets (i.e., Structures, Systems, and Components [SSCs]). The objective is to optimize the SSC replacement/refurbishment schedule in terms of economic constraints, data uncertainties, and SSC reliability data, as well to generate a priority list for maximizing returns on investment.

42 ENGINEERING↗
DOE OSTI2017

Instrument design optimization with computational methods

Using Finite Element Analysis to approximate the solution of differential equations, two different instruments in experimental Hall C at the Thomas Jefferson National Accelerator Facility are analyzed. The time dependence of density uctuations from the liquid hydrogen (LH2) target used in the Q wea k experiment (2011-2012) are studied with Computational Fluid Dynamics (CFD) and the simulation results compared to data from the experiment. The 2.5 kW liquid hydrogen target was the highest power LH2 target in the world and the first to be designed with CFD at Jefferson Lab. The first complete magnetic field simulation of the Super High Momentum Spectrometer (SHMS) is presented with a focus on primary electron beam deflection downstream of the target. The SHMS consists of a superconducting horizontal bending magnet (HB) and three superconducting quadrupole magnets. The HB allows particles scattered at an angle of 5:5 deg to the beam line to be steered into the quadrupole magnets which make up the optics of the spectrometer. Without mitigation, remnant fields from the SHMS may steer the unscattered beam outside of the acceptable envelope on the beam dump and limit beam operations at small scattering angles. A solution is proposed using optimal placement of a minimal amount of shielding iron around the beam line.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Chemical looping air separation with Sr 0.8 Ca0.2Fe 0.9 Co 0.1 O 3-δ perovskite sorbent: Packed bed modeling, verification, and optimization

Chemical looping air separation (CLAS) represents a promising approach for efficient O 2 production from the air. This present study aims at optimizing the absorber/desorber operations and the separation process with extensive experimental validation. Specifically, a one-dimensional packed bed model was developed to investigate the CLAS operation with a Sr 0.8 Ca 0.2 Fe 0.9 Co 0.1 O 3-δ perovskite sorbent. The redox thermodynamics of perovskite sorbent was measured by TGA and then incorporated into a linear driving force model to describe the O 2 absorption and desorption rates. Both 4-step and 5-step air separation cycle configurations, with various cyclic structures, were performed in a subpilot-scale packed bed. The model predicted O2 purity and productivity were consistent with experimental results, supporting its accuracy and applicability. Parametric analysis and multi-objective optimization were further carried out to assess the performance of CLAS. Both O 2 purity and recovery increased monotonically with the cycle time, airflow rate, steam flow rate, and absorption pressure. Meanwhile, optimal O 2 productivity and power consumption can only be achieved by specific combinations of these parameters. The optimized results showed that CLAS can be highly competitive when compared to conventional pressure swing adsorption (PSA) or cryogenic distillation. The 5-step cycle configuration achieved a minimum power consumption of 118 kW·h for producing 1 ton O 2 with ≥ 95% purity. The maximum O 2 productivity reached 0.0932 g O2 /(g sorbent ·h) with 390 kW·h/ton O 2 of energy consumption (95% pure). The optimization results also indicate that CLAS can potentially be more efficient than cryogenic distillation even when the required O 2 purity is above 99%.

42 ENGINEERING↗
DOE OSTI2022

Shell-Based Support Structure for the 45 GHz ECR Ion Source MARS-D

Superconducting electron cyclotron resonance ion sources (ECRISs) using NbTi coils and optimized for 28 GHz resonant heating have been successfully operated for almost two decades. Moving to higher heating frequencies requires increased magnetic fields, but traditional racetrack-and-solenoid ECRIS structures are at their limit using NbTi. Rather than moving to a superconductor untested in this field, we report the Mixed Axial and Radial field System (MARS) being developed at Lawrence Berkeley National Laboratory employs a novel closed-loop-coil design that more efficiently utilizes conductor fields and will allow the use of NbTi in a next-generation, 45 GHz ECRIS. This article presents the design of the shell-based support structure central to the MARS-D magnet design, as well as structural analysis of its components and optimization of pre-load parameters that will guarantee its successful operation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Mitigate: An Adaptive Network Data Anonymization Tool Using Condensation-Based Differential Privacy

Modern network devices collect a large amount of data that can be analyzed to identify bottlenecks, anomalies, cyber-attacks, etc. Therefore, there is often a need to analyze such collections of network data quite often by an external expert or by the research community. However, these collections of data contain sensitive, proprietary information. In order for the network data to be shared, it must first be anonymized. The overall objective of this project is to develop an innovative privacy management tool to anonymize network data and achieve sufficient privacy, acceptable data utility, and efficient data analysis at the same time. No existing anonymization methods can achieve all of these at the same time. The core of this technology is a differential private clustering algorithm that provides strong privacy protection, preserves data properties important for subsequent analysis, and allows the party receiving the anonymized data to conduct analysis directly on anonymized data without the need of decryption or any extra processing. The research carried out was to design, implement and verify a solution to this problem by completing the following tasks: 1) developing the core technology; 2) developing a context based method that automatically recommends fields that must be anonymized; 3) conducted experiments showing superior results using our approach compared to existing tools, and 4) developed an intuitive but basic user interface. The research that was conducted generated novel algorithmic techniques that utilize state-of-the-art methods such as condensation, differential privacy preservation, clustering, automated tuning based on contextual awareness, and recommendation techniques to specify columns to users for anonymization leading to optimal privacy that allows research analysis on the dataset. Experiments were conducted to evaluate the efficacy of these novel algorithmic techniques by performing analysis on original non-anonymized datasets, then conducting analysis on the same yet anonymized datasets and comparing the results of the analyses. Overall, the anonymized analysis results were within 1% of the original results, verifying that the generated technology not only guarantees a high level of privacy but also enables research analysis as if it were conducted on the original dataset. Potential applications of this technology include anonymization of any type of structured network datasets that contain sensitive identifiers, such as IP addresses, that can be used in multiple applications. For example, to create an AI or machine learning model for cyber security, e.g., to detect attacks, or for performance analysis, e.g., identify bottlenecks or predict performance. In addition, a market analysis that was conducted for potential applications of this technology identified a broader range of applications of our anonymization technology beyond the network sector that includes healthcare, banking, insurance, securities, finance (FISB), data brokering, cloud services, ad sales, and government.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

An Analysis of Concentrating Solar Power with Thermal Energy Storage in a California 33% Renewable Scenario (Report Summary) (Presentation)

This analysis evaluates CSP with TES in a scenario where California derives 33% of its electricity from renewable energy sources. It uses a commercial grid simulation tool to examine the avoided operational and capacity costs associated with CSP and compares this value to PV and a baseload generation with constant output. Overall, the analysis demonstrates several properties of dispatchable CSP, including the flexibility to generate during periods of high value and avoid generation during periods of lower value. Of note in this analysis is the fact that significant amount of operational value is derived from the provision of reserves in the case where CSP is allowed to provide these services. This analysis also indicates that the 'optimal' configuration of CSP could vary as a function of renewable penetration, and each configuration will need to be evaluated in terms of its ability to provide dispatchable energy, reserves, and firm capacity. The model can be used to investigate additional scenarios involving alternative technology options and generation mixes, applying these scenarios within California or in other regions of interest.

14 SOLAR ENERGY↗