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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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31 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

(U) Calculating First-Order Sensitivities to Material Density and Composition in Fixed-Source Problems Using the MCNP6 Perturbation Capability

The Taylor series (differential operator) perturbation method, as implemented in the PERT capability in MCNP6 (Ref. 1), can be used for first-order sensitivity analyses in fixed-source problems.2 Sensitivities of a response with respect to material and nuclide densities can be used for efficient first-order uncertainty quantification. This report discusses how to compute sensitivities of material densities and compositions in order to propagate uncertainties using the standard uncertainty propagation formula.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Data for Validating Models for PV Module Performance

This data encompasses performance data measured for flat-plate photovoltaic (PV) modules installed in Cocoa, Florida; Eugene, Oregon; and Golden, Colorado. The data include PV module current-voltage curves and associated meteorological data for approximately one-year periods. The data was acquired with the NREL Performance and Energy Rating Testbed (PERT) and the mobile Performance and Energy Rating Testbed (mPERT).

PV, Validation, IV Curves, Field performance, mPER↗
DOE OSTI2025

Enhancing lifetime, forecasting, and economic benefits of photovoltaic technologies undergoing UV-induced degradation with optical filtering

Ultraviolet-induced degradation (UV-ID) of various PV cell types was analyzed under optical UV filters with different cutoff wavelengths. Cell types studied included interdigitated back contact (IBC), passivated emitter and rear totally diffused (PERT), and heterojunction technology (HJT) based on crystalline Si (c-Si), and metal halide perovskite (MHP) cells. Analyzing degradation rates in two distinct regimes proved beneficial for all cell types. We used empirical linearizing functions ln(t) for c-Si technologies and 2 √t for MHP samples where t is time. These were applied to extrapolate UV-induced degradation over the lifetime of PV modules under various levels of optical UV filtering and used to predict the relative economic benefits for PV power plants. Degradation rates for all technologies were generally faster under the long pass optical filters having shorter cutoff wavelengths transmitting more UV irradiation and at elevated temperatures when testing MHP samples in the range between 60 °C and 90 °C.

14 SOLAR ENERGY↗
DOE OSTI2022

Module-Level Solutions For Degradation by Ionization Damage

After years of improving module efficiency while targeting mean degradation rates of 0.5 to 0.6 %/y for crystalline silicon technology, there is much evidence that the degradation rates are now increasing significantly. Contributing factors include:Radiation damage (UV-Light Induced Degradation): Trina solar: -4.5%/y degradation rate in Singapore, DOE National Laboratory Regional Test Centers showed degradation of -1% < r < -2%/y in crystalline silicon modules, Jinko Solar: -4% < r < -7% efficiency loss from 540 MJ/m-2 of UV-A light, ISFH: 15% relative power loss during of 1.8 GJ/m-2 UV exposure, attributed to H+. Electrical bias from positive system voltage (e.g., +1000 V, +1500 V) can drive ions and metallization through the encapsulation, NREL: Ion transport can affect the cell passivation, resulting in power loss of 5% to 40% in p-PERC+ (bifacial), NREL: Damage at cell rear with up to 17% power at cell fronts in n-PERT modules. Delamination can also occur due to cell surface reactions driven by light and bias.

module efficiency↗
DOE OSTI2023

Capacitance Transients, Photoconductive Decay, and Impedance Spectroscopy on 19% to 22% Efficient Silicon Solar Cells

High efficiency silicon solar cells are characterized using current-voltage curves, electroluminescence imaging, impedance spectroscopy, capacitance transients, microwave photoconductive decay, and time-resolved photoluminescence imaging. The sample set is composed of cells from different manufacturers and includes an n-type silicon heterojunction (SHJ), an n-type passivated emitter rear totally diffused (PERT), and five different p-type passivated emitter rear contact (PERC) cells. Carrier lifetimes, both photoconductivity and photoluminescence, are measured co-located with the light excitation pulse and within the cell but away from the light spot. Luminescence intensity and excess carrier lifetimes correlate to cell voltage. The capacitance transient time constants correlate to the capacitance values extracted from impedance spectroscopy.

capacitance↗
DOE OSTI2023

Preliminary verification of the MCNP perturbation and fixed-source tally sensitivity tools

Integral benchmark experiments are vital in the adjustment and validation of the nuclear data that govern predictive simulations across the nuclear community. The nuclear data sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®) transport code are currently limited; however, expanding sensitivity capabilities will allow benchmark experiments to be designed to resolve compensating errors and adjust nuclear data where previously prohibitively difficult. This paper provides details of a preliminary verification for the use of (i.) the recently revised perturbation and (ii.) developmental fixed-source sensitivity tools within MCNP to calculate sensitivities of tallied responses (such as current integrated over a surface, F1, and flux averaged over a cell, F4) to nuclear data in fixed-source simulations. Energy-binned and energy-integrated sensitivities calculated with these tools are compared against sensitivities calculated using a central-difference approximation. Here, the verification is completed for four configurations of a benchmarked system using a 4.5-kg plutonium sphere surrounded by varying amounts of copper and/or polyethylene. The results show that sensitivities calculated with the perturbation and fixed-source sensitivity tools agree with the central-difference-based approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Scaling Field-Theoretic Simulation for Multicomponent Mixtures with Neural Operators

Multicomponent polymer mixtures are ubiquitous in biological self-organization but are notoriously difficult to study computationally. Plagued by both slow single molecule relaxation times and slow equilibration within dense mixtures, molecular dynamics simulations are typically infeasible at the spatial scales required to study the stability of mesophase structure. Polymer field theories offer an attractive alternative, but analytical calculations are only tractable for mean-field theories and nearby perturbations, constraints that become especially problematic for fluctuation-induced effects such as coacervation. Here, we show that a recently developed technique for obtaining numerical solutions to partial differential equations based on operator learning, neural operators, lends itself to a highly scalable training strategy by parallelizing per-species operator maps. We illustrate the efficacy of our approach on six-component mixtures with randomly selected compositions and that it significantly outperforms the state-of-the-art pseudospectral integrators for field-theoretic simulations, especially as polymer lengths become long.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Preparation of cyclohexene isotopologues and stereoisotopomers from benzene

The hydrogen isotopes deuterium (D) and tritium (T) have become essential tools in chemistry, biology and medicine1. Beyond their widespread use in spectroscopy, mass spectrometry and mechanistic and pharmacokinetic studies, there has been considerable interest in incorporating deuterium into drug molecules1. Deutetrabenazine, a deuterated drug that is promising for the treatment of Huntington’s disease2, was recently approved by the United States’ Food and Drug Administration. The deuterium kinetic isotope effect, which compares the rate of a chemical reaction for a compound with that for its deuterated counterpart, can be substantial1,3,4. The strategic replacement of hydrogen with deuterium can affect both the rate of metabolism and the distribution of metabolites for a compound5, improving the efficacy and safety of a drug. The pharmacokinetics of a deuterated compound depends on the location(s) of deuterium. Although methods are available for deuterium incorporation at both early and late stages of the synthesis of a drug6,7, these processes are often unselective and the stereoisotopic purity can be difficult to measure7,8. Here we describe the preparation of stereoselectively deuterated building blocks for pharmaceutical research. As a proof of concept, we demonstrate a four-step conversion of benzene to cyclohexene with varying degrees of deuterium incorporation, via binding to a tungsten complex. Using different combinations of deuterated and proteated acid and hydride reagents, the deuterated positions on the cyclohexene ring can be controlled precisely. In total, 52 unique stereoisotopomers of cyclohexene are available, in the form of ten different isotopologues. This concept can be extended to prepare discrete stereoisotopomers of functionalized cyclohexenes. Such systematic methods for the preparation of pharmacologically active compounds as discrete stereoisotopomers could improve the pharmacological and toxicological properties of drugs and provide mechanistic information related to their distribution and metabolism in the body.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning

Monolayer films have shown promise as a lubricating layer to reduce friction and wear of mechanical devices with separations on the nanoscale. These films have a vast design space with many tunable properties that can affect their tribological effectiveness. For example, terminal group chemistry, film composition, and backbone chemistry can all lead to films with significantly different tribological properties. This design space, however, is very difficult to explore without a combinatorial approach and an automatable, reproducible, and extensible workflow to screen for promising candidate films. Here, using the Molecular Simulation Design Framework (MoSDeF), a combinatorial screening study was performed to explore 9747 unique monolayer films (116 964 total simulations) and a machine learning (ML) model using a random forest regressor, an ensemble learning technique, to explore the role of terminal group chemistry and its effect on tribological effectiveness. The most promising films were found to contain small terminal groups such as cyano and ethylene. The ML model was subsequently applied to screen terminal group candidates identified from the ChEMBL small molecule library. Approximately 193 131 unique film candidates were screened with approximately a five order of magnitude speed-up in analysis compared to simulation alone. The ML model was thus able to be used as a predictive tool to greatly speed up the initial screening of promising candidate films for future simulation studies, suggesting that computational screening in combination with ML can greatly increase the throughput in combinatorial approaches to generate in silico data and then train ML models in a controlled, self-consistent fashion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Investigating Fission Reaction Rate Ratio Sensitivities [Slides]

One EUCLID project goal is to create a NEW capability in the MCNP6 code. This is being tested on reaction rate sensitivities and compared with SENSMG results. Reaction rate ratio sensitivities were added to EUCLID sensitivity library and investigated to determine value toward designing optimized experiments aimed at reducing compensating errors in nuclear data. The use of adjustment using multiple responses (and underlying/required capabilities) may benefit many applications. These include a tool for adjustment using multiple integral responses (ND adjustment and validation community); sensitivities of additional responses (ND adjustment and validation community); sensitivity capabilities (users in many application areas including safeguards/nonproliferation, criticality safety, etc.); and experiment optimization capability (applications which can benefit from integral experiments). Team is working to build and test future tools and to understand compensating errors

235U↗
DOE OSTI2020

Latest Developments in PM Systems and Methods and their Application to WM Projects - 20364

How do you improve on an industry that is well established yet often misses the mark on key metrics demonstrating effective planning and execution of project scope, schedule and budget? With the increased complexity of DOE projects relative to either poorly kept records of what wastes are stored or the lack of specific knowledge relative to the waste concentrations/quantities, this is a question continually asked and investigated by many. In fact, in 2017, the GAO's report to Congress indicated that although the DOE has made some progress on its monitoring effectiveness and demonstrating progress criteria, these goals were not met and there needs to be more improvement and monitoring. This paper will offer some insights into the latest developments in project management methodologies and the possible application of these to waste management projects. Traditional data generated via a project schedule that utilizes critical path methodology (CPM) and additional earned value management (EVM) data needs to be accurate and enable the project manager to better understand the probability of project success. Although this data has readily been available on most large-scale projects, success as measured by various stakeholder groups including the client, project team, regulators, etc. is less than optimal. Therefore, an urgent need exists to explore how traditional project data (CPM and EVM) coupled with new methodologies allows for better planning and execution by the project team. Many new approaches/methodologies can even be used to predict the success of options prior to full implementation on the actual project. Three approaches/methodologies will be discussed: - Artificial Intelligence; - Change Management; - Blend of Traditional Management (Gantt chart) and Agile Methodologies. As market forces change, so will the direction of project management. The days of 'one size fits all' are no longer valid. A combination of predictive and adaptive approaches in the management of projects is essential to enable execution of project deliverables on time, under budget, and within the contractual scope. This paper is intended to provide the reader with insight to the close relationship of project management trends and business management trends, and to provoke critical thinking about what it means to align project management strategy with an environment of non-stop innovation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗