SEARCH · Engineering Papers

Results for “tool life”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2020

FY2019 Analysis Program Annual Progress Report

The VTO Analysis Program supports mission-critical technology, economic, and interdisciplinary analyses to assist in prioritizing VTO technology investments and to inform research portfolio planning. These efforts provide essential vehicle and market data, modeling and simulation, and integrated and applied analyses, using the unique capabilities, analytical tools, and expertise resident in the national laboratory system.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Power-to-Gas System Valuation. Final Report

To provide a framework for evaluating the technical and financial benefits of a power-to-gas (P2G) system deployed in the Holyoke Gas and Electric (HG&E) system, Pacific Northwest National Laboratory modified its energy storage valuation tools to run a one-year simulation of P2G operations. The simulation was used to evaluate the benefits of P2G for multiple grid and industrial applications over the economic life of the unit, or units, depending on the asset configuration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Editorial: Genomic insights on fungal hybrids

Hybrids are chimeric organisms that result from the crossing of two genetically divergent lineages. Compared to their parents, hybrids sometimes show higher adaptive capacities towards specific niches, thereby contributing to diversification (Abbott et al., 2013). Fungal hybrids have been neglected by formal studies for a long time due to the inherent challenges of the microbial species concept and the difficulty of identifying hybrids based on morphological characters (Gabaldon, 2020a; Boekhout et al., 2021). Although the first fungal hybrids were identified in Saccharomyces, thanks to careful dissection of metabolic properties (Morales and Dujon, 2012) and emerging genome sequencing technologies (Hittinger, 2013), it was the spread of these sequencing technologies that revealed the true pervasiveness of hybrids across the fungal tree of life (Naranjo-Ortiz and Gabaldon, 2020; Gabaldon, 2020b). Sequencing techniques, particularly genomic approaches, have not only unearthed the hybrid nature of many fungal organisms, but also serve as ideal tools for the study of hybrids. Hybrids have chimeric genomes, which usually display high instability and are subject to evolutionary pressures that are different from that of non-hybrid genomes (Runemark et al., 2019). Understanding how hybrids are formed, how they cope with their chimeric genomes, and how they evolve and adapt to distinct environments is a matter of intensive research. This Research Topic gathers six outstanding contributions that use genomic approaches to tackle diverse questions that relate to fungal hybrids.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

2.3.4.501 - Synthesis and Analysis of Performance-Advantaged Bioproducts

This project focuses on the synthesis and analysis of performance-advantaged bioproducts (PABPs). We have established collaborations with other BETO-funded projects and academic and industrial collaborators to source new molecules that have promising manufacturing pathways and that could be serve as performance-advantaged biochemicals or biopolymers. We conduct synthesis and characterization of biochemicals and biopolymers alongside techno-economic analysis and life cycle assessment to estimate their cost and environmental impacts relative to incumbent materials. As part of the project, Profs. Linda Broadbelt and Brent Shanks are developing computational pathway prediction tools to identify optimal production pathways for bio-based compounds via biological and chemo-catalytic transformations. When coupled to the polyID tool from the Inverse Design project, these tools will ultimately enable a narrowing of design space for PABPs. From FY21-FY23, we described a framework for benchmarking PAPBs, estimated the energy and GHG emissions for commodity organic chemicals, developed performance-advantaged nylons and polyesters from beta-ketoadipic acid, and produced lignin-based plasticizers. We have shown that aromatic amines can be used in performance thermosets and that polyhydroxyalkanoates with crosslinked side chains can exhibit rubber-like properties, along with repair and degradability. We are working actively with industry partners on scale-up and validation of multiple PABPs.

BIOMASS FUELS↗

DOE OSTI2020

Chapter 14: Sustainable Biomass Conversion Process Assessment

Process intensification and integration for sustainable design play an essential role in addressing and alleviating severe sustainable development challenges. It is prudent to evaluate a process design in its early stage development to ensure the process can achieve sustainability goals. The primary goal of a sustainability evaluation is to assess the impact of systems on areas sought to be protected and maintained over time, such as human well-being and ecosystems (Schaubroeck, T. and Rugani, B. (2017). A revision of what life cycle sustainability assessment should entail: towards modeling the net impact on human well-being. Journal of Industrial Ecology 21 (6): 1464-1477). Parenthetically, sustainable process design to convert biomass to fuels and chemicals plays an integral part in the bioeconomy sustainability. It is recognized that the integration of sustainability in process design is core to the mission in developing renewable fuels and should be considered a necessary practice in biorefinery design. This study demonstrates the use of Gauging Reaction Effectiveness for ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) as a tool to help track progress on process sustainability performance attributed to conversion improvement. With the incorporation of a wide range of indicators, GREENSCOPE captures the multi-dimensional aspect of the process design and operation. As opposed to conventional techno-economic analysis and life cycle assessment (in which the focuses are limited to economic and environmental aspects), GREENSCOPE enables the consideration of process intensification and integration for sustainable design. A high-octane gasoline production from woody biomass feedstock is used as a case study to demonstrate the approach.

biomass↗

DOE OSTI2025

From subsidies to stressors: Positively skewed ecological gradients alter biological responses to nutrients in streams

Abstract Subsidy–stress gradients offer a useful framework for understanding ecological responses to perturbation and may help inform ecological metrics in highly modified systems. Historic, region‐wide shifts from bottomland hardwood forest to row crop agriculture can cause positively skewed impact gradients in alluvial plain ecoregions, resulting in tolerant organisms that typically exhibit a subsidy response (increased abundance in response to environmental stressors) shifting to a stress response (declining abundance at higher concentrations). As a result, observed biological tolerance in modified ecosystems may differ from less modified regions, creating significant challenges for detecting biological responses to restoration efforts. Using the agriculturally dominated Mississippi Alluvial Plain (MAP) ecoregion in Mississippi, USA, as a case study, we tested the hypothesis that macroinvertebrate taxa that typically display a subsidy response to nutrient enrichment in less modified ecoregions (i.e., nutrient‐tolerance) shift to a stress response to increasing nutrients in highly modified watersheds with elevated baseline nutrient conditions (i.e., nutrient intolerance). The abundance and diversity of MAP‐specific intolerant taxa identified with threshold indicator taxa analysis were either unresponsive or exhibited a subsidy response to increasing nutrients in less modified ecoregions in Mississippi with less land alteration and lower nutrient concentrations, but declined at higher concentrations, providing evidence for a stress response to elevated nutrients in the MAP. Additionally, MAP‐specific tolerant and intolerant taxa richness responded to increased nutrients predictably and consistently across space and time within the MAP. However, in MAP streams, elevated specific conductance was predicted to dampen the response of tolerant and intolerant taxa richness to increasing nutrient concentrations, highlighting the importance of considering multistressor interactions when interpreting biological data. Lastly, we demonstrate the efficacy of this approach with sediment bacterial communities characterized with amplicon sequencing, which lack sufficient life history characteristics necessary for the development of multimetric indices. Both macroinvertebrate and bacterial communities responded similarly to increasing nutrient concentrations, suggesting DNA‐based approaches may provide an efficient biological assessment tool for monitoring water quality improvements in highly modified watersheds.

DeVilbiss, Stephen E. [U.S. Geological Survey Lowe↗

DOE OSTI2021

Reversible function switching of Ag catalyst in Mg/S battery with chloride-containing electrolyte

Rechargeable Mg/S batteries suffer from fast capacity decay because of the difficult re-oxidation of MgS. To tackle this problem, we used Ag catalyst in Mg/S cells with Cl- containing electrolyte, and achieved a greatly improved specific capacity of ~1200 mAh•g -1 and a long cycling life of 100 cycles. To understand the mechanism behind this improvement, we employed in-situ synchrotron radiation X-ray diffraction and in-situ X-ray absorption spectroscopy tools to study the reversible phase transitions during charge/discharge cycling. Additionally, the in-situ experiment results revealed that, at deeply charged state, Ag reacted with Cl- in the electrolyte to form the AgCl interfacial layer which prevented the physical contact of Ag with elemental S and avoided the formation of Ag 2 S; at early discharged state, AgCl transformed back to metallic Ag, which guaranteed its catalytic effectiveness for MgS decomposition. This reversible function switching mechanism of Ag catalyst is completely different from that in Mg/S cells using other catalysts or electrolytes.

25 ENERGY STORAGE↗

DOE OSTI2020

A genetic link between leaf carbon isotope composition and whole-plant water use efficiency in the C 4 grass Setaria

Genetic selection for whole-plant water use efficiency (yield per transpiration; WUE plant ) in any crop-breeding programme requires high-throughput phenotyping of component traits of WUE plant such as intrinsic water use efficiency (WUE i ; CO 2 assimilation rate per stomatal conductance). Measuring WUE i by gas exchange measurements is laborious and time consuming and may not reflect an integrated WUE i over the life of the leaf. Alternatively, leaf carbon stable isotope composition (δ 13 C leaf ) has been suggested as a potential time-ntegrated proxy for WUE i that may provide a tool to screen for WUE plant . However, a genetic link between δ 13 C leaf and WUE plant in a C 4 species has not been well established. Thus, to confirm if there is a genetic relationship in a C 4 plant between δ 13 C leaf and WUE plant under well watered and water-limited growth conditions, a high-throughput phenotyping facility was used to measure WUE plant in a recombinant inbred line (RIL) population created between the C 4 grasses Setaria viridis and S. italica . Three quantitative trait loci (QTL) for δ 13 C leaf were found and co-localized with transpiration, biomass accumulation, and WUE plant . Additionally, WUE plant for each of the δ 13 C leaf QTL allele classes was negatively correlated with δ 13 C leaf , as would be predicted when WUE i influences WUE plant . These findings demonstrate that δ 13 C leaf is genetically linked to WUE plant , likely to be through their relationship with WUE i , and can be used as a high-throughput proxy to screen for WUE plant in these C 4 species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

LANL Contributions to pyiron: An integrated development environment for computational materials science

To support and accelerate the development of simulation protocols in atomistic modelling, we introduce an integrated development environment (IDE) for computational materials science called pyiron (http://pyiron.org). The pyiron IDE combines a web based source code editor, a job management system for build automation, and a hierarchical data management solution. The core components of the pyiron IDE are pyiron objects based on an abstract class, which links application structures such as atomistic structures, projects, jobs, simulation protocols and computing resources with persistent storage and an interactive user environment. The simulation protocols within the pyiron IDE are constructed using the Python programming language. To highlight key concepts of this tool as well as to demonstrate its ability to simplify the implementation and testing of simulation protocols we discuss two applications. In these examples we show how pyiron supports the whole life cycle of a typical simulation, seamlessly combines ab initio with empirical potential calculations, and how complex feedback loops can be implemented. While originally developed with focus on ab initio thermodynamics simulations, the concepts and implementation of pyiron are general thus allowing to employ it for a wide range of simulation topics.

Janssen, Jan↗

DOE OSTI2025

Development of high throughput and in vitro assays for analyzing RNA modifications

Modifications on RNAs play major roles in their stability, translation, and enzymatic activity. Despite its importance, the current techniques are insufficient to study the structure and function of RNA modifications. Indeed, the National Academies of Science, Engineering and Medicine indicate that developing new tools and further study the function of RNA modifications is strategically a high priority for advancing science in the coming years (https://www.nationalacademies.org/our-work/toward-sequencing-and-mapping-of-rna-modifications). RNA modifications occur in all domains of life controlling processes such as RNA turnover, translation regulation, cellular defenses and bioproduction. Our preliminary data indicated that the insulin mRNA might get ADP-ribosylated by the ADP-ribosyltransferase PARP12. RNA ADP-ribosylation has been described in Escherichia coli. Combined to the fact that ADP-ribosyltransferase (PARP) genes are conserved throughout evolution we hypothesize that this modification might play essential roles in cells. Therefore, we proposed to develop sequencing techniques and in vitro enzymatic assays to identify and validate ADP-ribosylation motifs and sites. Here we report the development of RNA-seq and qPCR assays to identify ADP-ribosylated RNAs, in addition to a nicotinamide adenosine dinucleotide (NAD – ADP-ribosylation donor) consumption assay and an enzyme-linked immunosorbent assay (ELISA) to measure ADP-ribosyltransferase activity. Testing these assays with the insulin mRNA confirmed that this transcript is ADP-ribosylated. These assays will not only enable studying the function of ADP-ribosylation but can be easily adapted for studying other RNA modifications. This will open opportunities to study RNA modifications in different model systems from bacteria to viruses to plants, bringing insights into their cellular functions and the possibility of targeting them for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗

DOE OSTI2023

Biomimetic tissue phantoms for neurosurgical near-infrared fluorescence imaging

Neurosurgical fluorescence imaging is a well-established clinical approach with a growing range of indications for use. However, this technology lacks effective phantom-based tools for development, performance testing, and clinician training. Our primary aim was to develop and evaluate 3D-printed phantoms capable of optically and morphologically simulating neurovasculature under fluorescence angiography. Volumetric digital maps of the circle of Willis with basilar and posterior communicator artery aneurysms, along with surrounding cerebral tissue, were generated. Phantoms were fabricated with a stereolithography printer using custom photopolymer composites, then visualized under white light and near-infrared fluorescence imaging. Feature sizes of printed components were found to be within 13% of digital models. Phantoms exhibited realistic optical properties and convincingly recapitulated fluorescence angiography scenes. Methods identified in this study can facilitate the development of realistic phantoms as powerful new tools for fluorescence imaging.

3D modeling↗

DOE OSTI2022

Megawatt pulses from an all-fiber and self-starting femtosecond oscillator

Mamyshev oscillators produce high-performance pulses, but technical and practical issues render them unsuitable for widespread use. Here we present a Mamyshev oscillator with several key design features that enable self-starting operation and unprecedented performance and simplicity from an all-fiber laser. The laser generates 110 nJ pulses that compress to 40 fs and 80 nJ with a grating pair. The pulse energy and duration are both the best achieved by a femtosecond all-fiber laser to date, to our knowledge, and the resulting peak power of 1.5 MW is 20 times higher than that of prior all-fiber, self-starting lasers. Finally, the simplicity of the design, ease of use, and pulse performance make this laser an attractive tool for practical applications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

A validated thermal and biological model for predicting algal productivity in large scale outdoor cultivation systems

Proper assessment of the sustainability of algal products requires an understanding of algal growth rate with regional and temporal resolution. This study developed a bulk growth model that utilizes geospatial data, reactor geometry inputs, and a maximum of six strain-specific parameters to predict algal productivity with temporal and regional resolution. The model requires local weather data to calculate the time-resolved culture temperature which is combined with a biological model based on maximum theoretical carbon fixation to predict the time-resolved algal concentration. Validation of the model against experimental data illustrates an average ac- curacy of 0.27% ± 5.32% when comparing algal concentration at harvest over 45 days of cultivation data for Galdieria sulphuraria 5587.1, and Galdieria sulphuraria Soos grown in photobioreactors (PBRs) in Mesa, AZ (33.4152° N, 111.8315° W). For open raceway ponds (ORPs), an accuracy of 0.9% ± 2.35% was achieved when comparing algal concentration at harvest over 50 days of cultivation data for Chlorella vulgaris, Desmodesmus intermedius, Nannochloropsis oceanica grown in Atlanta, GA (33.7490° N, 84.3880° W) and Mesa, AZ (33.4152° N, 111.8315° W). The validation trials spanned three seasons (winter, spring, and summer) to ensure model ac- curacy throughout the year, and concentration between harvests was modeled with hourly resolution. The validated model is used to assess the productivity at several case-study locations in the United States with Chlorella vulgaris, grown in open raceway ponds and Galdieria sulphuraria grown in vertical flat panel photo- bioreactors. In conclusion, the model has been published as an open-source tool, in an effort to increase the fidelity of future studies that rely on outdoor algae cultivation for feedstock production and allow for time resolved results for future techno-economic and life cycle assessments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Prioritizing circular economy strategies for sustainable PV deployment at the TW scale

Global decarbonization requires an unprecedented scale-up of photovoltaic (PV) manufacturing and deployment. The material demand and eventual end of life management associated with multi-TW scale deployment poses many challenges. Circular Economy (CE) and it's associated R-Actions (Reduce, Reuse, Recycle) have been proposed to mitigate end of life management and material sourcing concerns. However, CE metrics typically focus on a single product and only consider mass, excluding energy flows. This work leverages the PV in Circular Economy (PV ICE) tool to quantify the deployment, mass, and energy impacts of R-Actions and proposed sustainable PV designs in the context of achieving energy transition deployment goals (75 TW in 2050). 13 module scenarios are established and evaluated across 6 capacity, mass and energy metrics to identify tradeoffs and priorities. We find that increasing module efficiency can reduce near-term material demands up to 30% and improve energy metrics by up to 9%. Material circularity (recycling) can minimize lifecycle wastes and reduce material demands at the cost of higher energy demands. Increasing module lifetime, including reliability improvements and reuse strategies, is effective at reducing both material (>10%) and energy demands (24%). Uniquely, lifetime improvements maximize benefits and minimize the harms across all six metrics while achieving multi-TW scale deployment.

Photovoltaics↗

DOE OSTI2020

PV O&M Cost Model [SWR-21-14]

This tool presents a method for calculating costs associated with the operation and maintenance (O&M) of photovoltaic (PV) systems. The tool compiles details regarding the cost and frequency of multiple O&M services to estimate annual O&M costs ($/year) for each year of an analysis period, the net present value ($) of life cycle costs accumulated over the analysis period, and the reserve account amount ($) that might be required to fund unexpected repairs. The reserve account includes parts inventory and is important for providing a source of funds to make repairs quickly and avoid lost production. This method allows a detailed selection of services to perform based on system size, market served (e.g., residential, commercial, or utility), type and configuration of system components (e.g., micro-, string, or central inverter), and site and environmental conditions (e.g., pollen, bird populations) which is an improvement over simple per unit valuations of O&M costs ($/kW/year). This model also distinguishes costs that vary from year to year and increase at different rates over time as modeled by heuristic failure distributions (e.g., Weibull or Lognormal distribution) based on actuarial data for many of the services.

Walker, Andy↗

DOE OSTI2022

A Demonstration of Intelligent Container Surveillance Using Stationary and Mobile Camera Platforms

Surveillance of nuclear material storage containers is required to ensure that the container safety boundary is maintained during the service life of the container. As many of these container types are the first and only containment barrier to release protecting the worker, public, and environment, it is imperative to develop robust surveillance tools to characterize container degradation. Machine learning (ML) techniques have matured quickly in the past decade and are slowly becoming a routine application in data analysis. While more popular architectures have been developed with different applications in mind, these can be easily translated to container surveillance requirements. In this study, we developed a ML model based on the Detectron2 framework to identify slip lid containers and common exterior container defects, primarily dents. Commercial-off-the-shelf cameras are combined into a stationary camera array or are mounted to a robotic arm to provide more mobility for positioning needs. Results from the model evaluations on the images indicate that the stationary camera arrays outperform the accuracy of the mobile camera systems for both individual camera and composite image detections. Overall, however, the detection accuracies of the systems fell short of 50% and were less than satisfactory. Future efforts to improve the system involve focusing on a single camera deployable solution that combines a controllable light source that eliminates one of the biggest environmental factors that influence ML model detection performance. Additional training set collection is planned to build a more robust model that enables accurate detection from a wider range of imaging conditions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2024

An Ultra-Stable Reference Electrode as In-Situ System Diagnostics Tool for Redox Flow Batteries - CRADA 634 (Abstract)

The objective of the proposed project is to develop and demonstrate an ultra-stable reference electrode (RE) technology as an in-situ system diagnostics tool integrated in kW scaled commercial vanadium redox flow battery (VRFB) stacks for long-duration energy storage (LDES) applications and to advance its commercialization, with expected cell reliability enhancement in stack life increase of 6-10 % and levelized cost of storage (LCOS) reduction of 5-8 %. In this project, PNNL will partner with Stryten Energy LLC, with a total budget of $250K and 50% cost share for one year.

25 ENERGY STORAGE↗