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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

PV Module BOM and Test Data

This dataset contains compiled results from annual PV Module Reliability Scorecards published by PV Evolution Labs – also known as PVEL. These scorecards show summary results of PV module testing performed by PVEL and name specific models of PV modules as "Top Performers" in various tests. Full details on testing, Top Performer status and other criteria for inclusion in Scorecards are documented in reports and online documentation available from https://www.modulescorecard.pvel.com. This dataset is not affiliated with PVEL and is intended only to simplify sorting and filtering Scorecard data and finding specific PV module models and Top Performer results. Note that data included in Scorecards has evolved over time, so not all data is available for all years, and testing protocols and Scorecard criteria have been changed over time.

14 SOLAR ENERGY↗
DOE OSTI2024

Baseline status of BOM instruments at Kennaook Cape Grim

When utilizing these data from Kennaook Cape Grim please acknowledge the Australian Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for their long-term and continued support of the Kennaook Cape Grim Baseline Air Pollution Monitoring Station. In addition, please contact the Lead Scientists responsible for the collection of these data sets (stuart.baly@bom.gov.au, melita.keywood@csiro.au, ruhi.humphries@csiro.au and Erin.dunne@csiro.au) to discuss collaboration and authorship opportunities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Solar Photovoltaic (PV) Manufacturing Expansions in the United States, 2017-2019: Motives, Challenges, Opportunities, and Policy Context

This report analyzes U.S. PV manufacturing announcements from 2017 through July-2019 and explores the potential impact of tariffs on the competitiveness of U.S. PV module manufacturing. First, the fraction of announcements that resulted in established facilities in the time frame specified is analyzed, as well as firm nationality and the existence of any other U.S. facilities for the firm. The prevalence of different PV product types among the announcements was also analyzed, as well as the type of facilities selected for development (greenfield, existing PV factories, or repurposed buildings). The cost to build these facilities was also analyzed in the context of their capacity, the value of incentives received by state and local governments, and the number of jobs created. Case studies of Auxin Solar, First Solar, Hanwha Q Cells, JinkoSolar, LG, Silfab, Solaria, and SunPower were conducted and highlight five factors influencing firms’ decisions to expand their U.S. PV production capacity. These included: 1) proximity to demand, including supply contracts and demand for domestic content 2) tariffs and other incentives. The Section 201 tariffs on PV module imports were often described helpful but tariffs on cell imports (Section 201) or materials (Section 301, Section 232) were often described as counterproductive since U.S. supply chains do not exist for many necessary goods. The corporate tax decrease and local incentives were often mentioned as helpful. 3) the ability to move quickly in order to maximize the benefit of the Section 201 tariffs. This affected decisions to select localities with faster permitting or moving into existing buildings. 4) competition with scale, where competing with Asian PV imports or avoiding imports of material from China was challenging due to the larger scale of Asian manufacturers. Additionally, smaller firms expressed concerns that larger firms may not need their U.S. facilities to profitable. 5) access to capital, which was a particular challenge for smaller firms. Several U.S. tariffs affect the economics of PV cells, modules, and balance-of-module (BOM) materials, some of which are applicable to a long list of countries and others applicable only to China or Taiwan. We analyze how the tariffs interact to affect the prices of c-Si modules sourced under various assumptions about domestic and imported components and assembly. We estimate module prices under a range of baseline scenarios featuring U.S.-assembled modules with Southeast Asian cells (not from China or Taiwan). When all BOM components are sourced from the United States, baseline module prices are $0.37/W (below the 2.5-GW Section 201 cell cap) to $0.42/W (above the 2.5-GW cell cap). If all BOM components are sourced from China, the module price in this baseline U.S.-assembly scenario can reach up to $0.60/W. Imported module prices are lower than or within the range of the U.S.-assembled baseline prices under some conditions. Importing bifacial modules from Southeast Asia is the lowest-priced alternative, at $0.35/W, because bifacial modules are excluded from the Section 201 tariffs. Importing Southeast Asia modules that contain U.S. cells results in a price of $0.38/W, also owing to a Section 201 exclusion. Importing Southeast Asian modules that have Southeast Asian cells yields a price of $0.44/W, and importing Chinese modules that have U.S. cells yields a price of $0.58/W. These results suggest that U.S. tariff policy in 2019 may encourage U.S. assembly of mono-facial c-Si modules if the 2.5-GW cell import cap is not reached and Chinese BOM imports are negligible. However, some imported module options may offer the lowest prices if the 2.5-GW cell import cap is reached and/or U.S. module manufacturers must rely on significant Chinese BOM content. The analysis shows the 2.5-GW cell cap may be exceeded in 2019 and following years. It is also likely that U.S. module manufacturers will need to use at least some Chinese BOM content, since U.S. module manufacturers have stated that U.S. supply chains do not exist (or do not exist at a sufficient scale) for most BOM components, which makes them at least partially reliant on Chinese BOM and thus subject to Section 301 tariffs.

14 SOLAR ENERGY↗
DOE OSTI2022

Strengthening the Security of Operational Technology: Understanding Contemporary Bill of Materials

The evolution of cyber-physical infrastructure has made its security more challenging. The last few years have witnessed a convergence of hardware and software segments in various domains, including operational technology (OT) which is responsible for carrying out critical tasks such as monitoring and controlling power grids, nuclear plants, transportation, and emergency services. Both hardware and software encapsulate numerous open source and proprietary subcomponents, making it crucial for end-users to understand the composition of the products they are using. For example, wind turbines incorporate thousands of lines of code (software) used for the turbine's design, planning, operation, and analytics in addition to the numerous hardware subcomponents that construct it. Due to the highly complex nature of software and hardware, knowledge of the components and subcomponents is required to mitigate cyber vulnerabilities and defend against cyberattacks. There has also been a transformation from a traditional linear supply chain into a global, dynamic, diverse, and interconnected system. The digitization of the supply chain makes it easier to find and exploit vulnerabilities. Critical infrastructures (e.g., power grids, oil, natural gas, water, and wastewater) rely on OT to function, and if the OT is compromised, equipment damage and potential interruption of services could result. A significant security measure to protect OT systems from disruption is to develop a supply chain bill of materials (BoM) corresponding to the software and hardware used in OT, along with attestations amongst vendors and asset owners. A supply chain BoM is a proactive way to understand the inherent vulnerabilities in the system and mitigate them in advance of being exploited. BoMs bolster the trust placed in the digital infrastructure and enhance software supply chain security by sustaining the management of component obsolescence and compliance, along with the seclusion of unsafe segments of a specific product. Adopting BoM tools is becoming increasingly important across various government sectors, as evidenced by the recent U.S. executive order on cybersecurity (NIST 2021). This paper aims to classify BoMs based on structure, functionality, component type, and architecture. The work also discusses case studies to further highlight the benefits of BoMs. In addition, it identifies missing pieces in existing BoM implementations so that future research may identify bounds on where it could expect to make improvements and directly enable researchers to identify promising areas for exploration. Further, the authors provide valuable recommendations to tool developers, researchers, and standardizing organizations (policymakers), additionally benefitting critical infrastructure owners and government executives. This aids in paving a path for future work, thereby, providing suggestions to determine a tool for consumers that best suit their needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Visualizing Comparisons of Bill of Materials

Protecting critical infrastructure from cyber attacks, natural disasters, and other disruptions is a priority of the U.S. Government. Critical infrastructure includes providing electricity to homes and businesses, supplying natural gas for heating, and producing renewable energy sources. A loss of these services, as seen in the Solarwinds supply chain attack in 2020 , Texas snowstorm of 2021, the Colonial Pipeline cyber incident of 2021, and the Washington power substation attacks in 2022 result in high costs to consumers, disruption of everyday life, and even death. To protect the infrastructure, we first have to know what equipment we are protecting. The complexity of distributed manufacturing and development coupled with the increasing prevalence of cyber and supply chain attacks necessitates a greater understanding of the hardware and software components that comprise equipment in critical infrastructure. When a vulnerability in a single software library can have disastrous consequences, it is vital to understand critical equipment and systems at a granular level. This need has led to increased energy around the development and incorporation of bill-of-materials (BOM) into existing asset management practices to aid in mitigating, and responding to future attacks \cite{noauthor_software_nodate}. While much of the current research is devoted to creating BOMs, it is equally important to develop methodologies for leveraging BOMs to answer questions, such as: How has my software changed? Are two pieces of equipment equivalent? Does this piece of equipment that just arrived match my historical information? In this work, we demonstrate how BOMs can be represented by graph structures. We then describe how these structures can be fed into a graph comparison algorithm to produce a novel interactive visualization that allows us to not only identify differences in BOMs, but show exactly where they are in the product.

Jones, Rebecca D.↗
DOE OSTI2026

Evaluation of Hardware and Software Bill of Materials (HBOMs/SBOMs) Extraction Methods

Hardware and software bills of materials (HBOMs and SBOMs) provide important visibility into the components, dependencies, and supply chain relationships within programmable digital devices. This visibility is critical for advanced nuclear reactor applications, where use of common or shared hardware components, software libraries, suppliers, or manufacturing processes may create common cause failure (CCF) vulnerabilities despite apparent diversity. This paper evaluates current approaches for obtaining and analyzing HBOMs and SBOMs in support of CCF, diversity and defense-in-depth (D3) assessments, and begins to explore potential methods for artificial intelligence/machine learning-based analysis. The availability of BOM information from advanced reactor manufacturers and vendors, representative hardware and software categories found in advanced reactor systems continues to limit research [13]. This paper compares commonly used BOM formats, including CycloneDX, SPDX, and SWID. It also surveys publicly available tools for generating BOMs from source code, compiled binaries, and hardware-related information, noting limitations in language coverage, system age, and format interoperability. Finally, this paper evaluates methods for correlating BOM data with vulnerability and exploitability information, including VEX, CVE, and CWE resources. The findings indicate that publicly available nuclear-vendor BOMs are limited, making third-party extraction and research into novel analysis techniques necessary.

Cybersecurity↗
DOE OSTI2022

Correspondence: Bill of Materials Variation and Module Degradation in Utility-Scale PV Systems

We report photovoltaic (PV) modules of the same make and model are often assembled with different bills of materials (BOMs). In this correspondence, we revisit two case studies of utility-scale silicon PV systems in which these differing BOMs were associated with faster-than-expected degradation. In one of the sites, we found that different metallization paste had been used for grid lines in some cells leading to loss of contact to the cell and severe series resistance degradation. We provide details on the observation of this mechanism at two additional sites not described in the original article. In a second case study, we found that two different types of cell had been used, and that they could be distinguished by their back contact. Cells with uniform back contacts suffered from light and elevated temperature induced degradation (LeTID), while those with local back contacts did not. We also briefly describe BOM variations observed at other sites to illustrate the extent of the challenge. Our results from both sites underscore that variations in BOM, even among modules of the same make and model can lead to reliability challenges.

14 SOLAR ENERGY↗
DOE OSTI2022

Towards Software Bill of Materials in the Nuclear Industry

Large, modern industrial facilities often incorporate thousands of digital assets in their operational technology. Regulated facilities, such as nuclear power plants (NPPs), maintain robust cybersecurity and configuration management programs that often use bills of materials (BOMs) for these assets, including make, model, and version of hardware, firmware, and software. However, these BOMs typically capture only first- or second-tier information provided by the original equipment manufacturer (OEM). Unfortunately, as indicated by the increasing number and sophistication of software supply chain attacks, this level of detail is insufficient for identifying all the potential vulnerabilities and risks in software applications. Software BOMs (SBOMs) provide detailed enumeration of components and dependencies within the product or devices, including firmware. SBOMs can be combined with vulnerability data sources and vendor vulnerability attestations to improve vulnerability management and enable rapid identification of affected components when new software vulnerabilities are discovered. Ideally, SBOMs are created by the OEM prior to installation. However, since this practice is not yet commonplace and since NPPs are typically slow to adopt new technology, most NPPs do not incorporate SBOMs into their asset or configuration management programs. Fortunately, SBOMs can be generated by NPPs on existing digital assets to provide further insight into risk management decisions. This report provides an overview of the current SBOM ecosystem and recommends guidance on how to get started in a “crawl, walk, run” manner to develop and implement a sustainable SBOM program for digital assets in an NPP.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1992

Visualization and modeling of factors influencing visibility in computer-aided crewstation design

We have developed two modules for use in computer-aided design (CAD) of crewstation environments that enhance the designer's appreciation of factors influencing the pilot's vision and visual processing capacity. The Binocular Optics Module (BOM) is an interactive tool for visualizing geometric aspects of (1) how retinal imagery of the environment changes on the pilot's retinas under conditions of eye and object motion, and (2) how visual capabilities that can be modeled as regions or contours on the retinas, affect spatial perception of the environment. The Visual Performance Module (VPM) contains a signal processing model of human visual discrimination that quantitatively predicts visual discrimination performance. The outputs of the VPM are retinal contours that represent performance probabilities. These contours may be used as inputs to the BOM for visualizing those volumes of space within the crewstation that bound different levels of the pilot's of visual discrimination capability. Used together, the BOM and VPM provide the designer with the opportunity to interactively explore relationships between environmental retinal imagery and visual function, and the ability to factor the pilot's visual capabilities into the earliest phases of crewstation CAD.

Arditi, Aries↗
DOE OSTI2024

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗
DOE OSTI2022

Economic and embodied energy analysis of integrated circuit manufacturing processes

Integrated circuits (ICs) are the fundamental microelectronic building blocks of typical information and communication technology (ICT) devices such as laptops and smartphone. With the emergence of faster and cheaper low-power ICs for the growing ICT market, there is a limited information on their manufacturing energy and economic impacts owing to the lack of recurrent upgradation of proprietary IC manufacturing process data. In this work, economic and life cycle energy assessments (LCAs) of IC manufacturing and assembly processes were conducted using the latest bill of materials (BOM) manufacturing data in a state-of-the-art IC manufacturing cost software tool developed by IC Knowledge, LLC. IC manufacturing cost was estimated to be $\$$1.00-$\$$5.00/cm 2 ; the high-end cost represents the most advanced 3D NAND IC technology with the Wafer Level Chip Scale Package cost of $4/cm 2 . Total cumulative energy demand (CED) estimates of IC manufacturing using the OpenLCA software ranged from 9 to 38 MJ/cm 2 or 56–235 BJ/month with the largest share (~ 75%) from on-site energy. The IC manufacturing CED is projected to increase with the progress in IC technology node, which has increased by more than two times for technology node evolution from 110 to 14 nm. Furthermore, the representative detailed BOM data were considered to reduce the CED uncertainties of the estimated standard deviation of 35%- 42%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

CyProduct: A software tool for accurately predicting the byproducts of human cytochrome P450 metabolism

In silico metabolism prediction is a cheminformatic task of autonomously predicting the set of metabolic byproducts produced from a specified molecule and a set of enzymes or reactions. Here we describe a novel machine-learned in silico cytochrome P450 (CYP450) metabolism prediction suite, called CyProduct, that accurately predicts metabolic byproducts for a specified molecule and a human CYP450 isoform. It includes three modules: (1) CypReact, a tool that predicts if the query compound reacts with a given CYP450 enzyme; (2) CypBoM, a tool that accurately predicts the “bond site” of the reaction (i.e., which specific bonds within the query molecule react with the CYP isoform); and (3) MetaboGen, a tool that generates the metabolic byproducts based on CypBoM’s bond-site prediction. CyProduct predicts metabolic biotransformation products for each of the nine most important human CYP450 enzymes. CypBoM uses an important new concept called “Bond of Metabolism” (BoM), which extends the traditional “Site of Metabolism" (SoM) by specifying the information about the set of chemical bonds that is modified or formed in a metabolic reaction (rather than the specific atom). We created a BoM database for 3487 CYP450-mediated Phase I reactions, then used this to train the CypBoM Predictor to predict the reactive bond locations on substrate molecules. CypBoM Predictor’s cross-validated Jaccard score for reactive bond prediction ranged from 0.380 to 0.452 over the nine CYP450 enzymes. Over variants of a test set of 72 known CYP450 substrates and 30 non-reactants, CyProduct outperformed the other packages -- including ADMET Predictor, BioTransformer and GLORY -- by an average of 200% (wrt Jaccard score) in terms of predicting metabolites. The CyProduct suite and the datasets are freely available at https://bitbucket.org/wishartlab/cyproduct/src/master/.

Machine learning, Cytochrome P450, Metabolism pred↗
DOE OSTI2022

Storm DEPART(Damage Estimate Prediction And Recovery Tool)

Damage prediction, materials needed, and resource allocation modeling capability in order to support pre-incident planning and preparation by predicting damage to the power generation capacity, transmission grids, distribution networks, and communications assets. The capabilities will be developed by multiple factors to include wind bands, storm surge, and flooding forecasts to participant’s assets which will result in a report of predicted damages. Additional factors to include available participants infrastructure data to include class, age, construction, location, wind rating, and additional information not in the public domain. Based on predicted damages, the output will be a bill of materials (BOM) to support short-term recovery operations. The extensiveness and level of detail for this BOM will depend on the replacement configuration specifications provided for each individual participant asset. Any limiting factors for the model will be applied related supply chain and resource constraints.

Klett, Mary↗
DOE OSTI2021

Additively Manufactured Solid-State Luminaire

This project addresses several key barriers to wide-spread adoption of additive manufacturing (AM) technology as applied to solid state lighting luminaires. The solution will utilize cutting edge AM approaches for integrating structure with thermal management solutions, electronic functionality, and optics. The research team (Eaton, Lighting Research Center (LRC) at Rensselaer Polytechnic Institute, Xerox Research Centre of Canada (XRCC)) utilize their AM and lighting expertise to investigate breakthrough manufacturing approaches that will significantly reduce cost, eliminate manufacturing process waste, and improve luminaire efficacy. The team has identified critical areas of research and proposed novel technical approaches to achieve these goals. Key areas of focus in Budget Period 1 (BP1) of the project quantified the impact of applying AM methodologies to the main, discrete subsystem components (Heat Sink, Housing, Optics, Electronics). Budget Period 2 (BP2) research explored similar impact on a fully integrated, AM modular luminaire concept. Final Achievement of the Target Metrics for the project are as follows: Material Reduction: achieved > 57.45% (target is 50%) Manufacturing Process: achieved > 51% reduction (target is 50%) Application Efficacy: achieved 126 lm/W (target is 130 lm/W) First Cost vs Baseline: demonstrated 49% improvement in project timing, 59% improvement in man hour savings and 89% worse BOM costs (due to deficiencies in current “state of the art” equipment). The BOM costs improve to 53% savings if state of the art processes and equipment could have been used.

3D Printing↗
DOE OSTI2022

Magnetic Gears: The Key to Robust, Cost-Effective Hydropower Drivetrains

Based on previous demonstrated success at fabricating 5 and 10 kW scale magnetic gearbox (MGB) prototypes, Emrgy and its partners (the project team) proposed to design and construct a 100 kW scale MGB with a 30:1 gear ratio for the low-head hydro applications. The Statement of Project Objectives included tasks covering: 1) Market Applicability; 2) Technical Metrics; 3) Design (initial); 4) Electromagnetic (EM) Load and Structural Analysis; 5) Modal Analysis; 6) Sealing Design and 7) Final Design during Budget Period 1. Budget Period 2 included tasks covering: 1) Materials Procurement and Test Plan Development; 2) Assembly; and 3) Testing. The Market Applicability study (Task 1) led to a clear conclusion and recommendation toward “Low Head” technologies for maximum market share of both New Stream Reach development as well as powering Non-Powered Dams. The findings of this study also identified the opportunity for a larger scale magnetic gearbox-based drive train as a function of increased torque, as opposed to increased speed. The Technical Metrics Study (Task 2) concluded a horizontal orientation was preferred, examined potential loss mechanisms, concluded that a Halbach Array magnetic design was preferred, established a 30:1 gear ratio as optimal, and established a power rating of 100 kW as optimal. The subsequent initial and final detailed design process included electro-magnetic (EM) load and structural analysis (Task 4), a Modal analysis (for vibration) (Task 5), and a sealing design (Task 6) to assure water impermeability. The final design package (Task 7) included 729 individual parts, 117 unique part numbers, and 15 assemblies. In order to facilitate procurement, the full bill of materials was broken down into several sub-components: 1) custom magnetic parts; 2) custom machined parts; 3) custom casted parts; and 4) commercial off the shelf (COTS) parts. The casted parts were fabricated by Oak Ridge National Laboratory (ORNL) via a Cooperative Research and Development Agreement (CRADA) with Emrgy and funded by the Advanced Manufacturing Office (AMO). The procurement effort (Task 8) ultimately covered three time periods based on challenges encountered in meeting the budgeted cost for the prototype. Following the first effort in the early stages of Budget Period 2 in 2017, a no-cost time extension was granted to seek alternative fabrication and procurement options. The project was re-booted in 2020 based on the new ORNL CRADA that would focus on five (5) of the more difficult and expensive parts using their advanced manufacturing expertise. Procurement efforts for the other custom machined parts resulted in quotations that still exceeded the budget by more than $\$$100k. This was, in part, also due to the concurrent COVID-19 pandemic that caused both supply chain disruptions and labor shortages. As the project continued, pricing and availability degraded further. In Q2 FY’22, it was decided to not proceed with the fabrication of the prototype (Task 9) based on budgetary limitations. Outcomes included a full and detailed design of a 100 kW magnetic gearbox and associated indented bill of materials (BOM) and CAD drawings, a full assembly instruction manual with an associated BOM for materials necessary to support assembly, the fabrication of the double Halbach magnetic array for the rotor/stator system, fabrication of five (5) sand-casted/machined parts (via CRADA with ORNL) and an initial draft of a comprehensive testing plan. The most significant non-outcome was the actual fabrication and testing of the prototype gearbox based on budget limitations. Lessons learned included the need for an Application / Design / Cost trade analysis to better elucidate the cost potential of the MGB in the projected volumes anticipated for future demand. This would better establish the efficacy of the original cost target ($\$$0.80/Watt) and/or the need for reconsideration of designs and applications. Likewise, additional consideration of the prototype nature of the gearbox – single use, short lifetime, etc. - either as a separate exercise or in place of the design process completed, to reduce the cost of the demonstration prototype device. Additionally, project continuity was cited as a significant risk based on the loss of the primary design engineering firm after Budget Period 1. A design analysis exercise was conducted at the conclusion of the project to identify potential areas for cost reduction. One concept considered was the removal of the inner ring of magnets (with associated changes in the outer ring magnets) to enable a horizontal collapse of the design. It was estimated this could reduce cost by 10-25% without impacting performance.

13 HYDRO ENERGY↗
DOE OSTI2023

Tansey_MICRE_AAD_lidar_cloud_and_precip_phase_V2.0_20160406_201601120

This data file contains retrievals of cloud-base and below-cloud precipitation phase base for the MICRE campaign. The retrieved base is largely based on AAD depolarization lidar measurements. BOM cloud radar (BASTA), ARM ceilometer, and U. Canterbury ceilometer data are used to locate cloud base and below-cloud precipitation. Details on the algorithm and analysis of results are given in Tansey et al. 2023 (submitted DOI: 10.22541/essoar.168394768.89694625/v1). The data is limited to the period 20160406 to 201601120 during which both AAD lidar data and BoM radar data was collected.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Advanced Stirling Convertor (ASC-E2) Performance Testing at NASA Glenn Research Center

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) has been supporting development of the Advanced Stirling Radioisotope Generator (ASRG) since 2006. A key element of the ASRG Project is providing life, reliability, and performance testing of the Advanced Stirling Convertor (ASC). For this purpose, four pairs of ASCs capable of operating to 850 C and designated with the model number ASC-E2, were delivered by Sunpower of Athens, OH, to GRC in 2010. The ASC-E2s underwent a series of tests that included workmanship vibration testing, performance mapping, and extended operation. Workmanship vibration testing was performed following fabrication of each convertor to verify proper hardware build. Performance mapping consisted of operating each convertor at various conditions representing the range expected during a mission. Included were conditions representing beginning-of-mission (BOM), end-of-mission (EOM), and fueling. This same series of tests was performed by Sunpower prior to ASC-E2 delivery. The data generated during the GRC test were compared to performance before delivery. Extended operation consisted of a 500-hour period of operation with conditions maintained at the BOM point. This was performed to demonstrate steady convertor performance following performance mapping. Following this initial 500-hour period, the ASC-E2s will continue extended operation, controller development and special durability testing, during which the goal is to accumulate tens of thousands of hours of operation. Data collected during extended operation will support reliability analysis. Performance data from these tests is summarized in this paper.

Oriti, Salvatore↗
NASA NTRS2011

United Space Alliance, LLC Windchill As-Built Highlights

Work Order execution data from Solumina As Worked BOM (As-Built) in Solumina (Slide 2) sent to Windchill Windchill receives As Worked BOM data and 'marries' the Solumina execution data to the Part Instance/Product Structure/As-Design (Slide 3 As-Design and Slide 4 &5 As-Built) Manage the As-Built to As-Design delta's via the interface and Part Instance Attributes (Slide 6) including Work Order data and any CMcomments Produce an As-Built to As-Design report that also includes all Part Instance Attribute data (no screenshot as this is still in development) Utilize Windchill and Solumina 'Out of the Box' functionality

Richmond, Dena M.↗