The ''Disadvantaged'' - Unemployable or just unemployed?. A report on training for university employment
Job training, urban studies and socio-economic participation at University of California
Zwerling, S.↗
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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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Geospatial analysis of freight accessibility and job attraction: The role of interstate ramps, airports, ports, and rail
The number of jobs within an industry is significantly influenced by geographical location, with transportation infrastructure playing a key role. While previous research has largely focused on how access to jobs affects employment, less attention has been given to how transportation infrastructure impacts business operations and job attraction. Here, this study addresses this gap by examining how the ease of transporting products to key transportation facilities affects job numbers in freight-intensive industries. Using job data from the Longitudinal Employment Household Dynamics dataset at the Census Tract level, we applied a non-parametric model to assess the impact of proximity to interstate ramps, rail intermodals, ports, and airports. Our analysis revealed that closer transportation infrastructure generally has a greater impact on employment. Specifically, interstate ramps are crucial for attracting jobs, particularly in rural areas, while airport proximity is essential for industries dealing with high-value, time-sensitive goods, as seen notably in Massachusetts. The importance of transportation facilities varies considerably across states and industries. The findings and method in this study can be used by transportation agencies for freight planning.
99 GENERAL AND MISCELLANEOUS↗
Equitable Electrification Analysis for Existing Buildings in Richmond, CA [Slides]
Since June 2022, NREL has provided technical assistance in the form of research and analysis in order to support the City of Richmond in identifying strategies to equitably transition its existing buildings from reliance on natural gas to clean electricity. Building on data from the ResStock and ComStock tools, the analysis looked at the potential impacts of building envelope and electrification improvements on energy consumption and greenhouse gas emissions, residential utility bills, jobs and employment, and indoor air quality. This presentation summarizes the findings from that research and analysis.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Employment access assessed using the mobility energy productivity (MEP) metric
Transit agencies, local governments, employers, and job-seekers have a shared interest in connecting residents with jobs in an affordable and time efficient manner, with public agencies also caring about energy efficiency and air quality. Employment hubs are an opportunity to solve the spatial mismatch between homes of job-seekers and the locations of desirable jobs. Such is the case in Columbus, Ohio, between Rickenbacker Industrial Park and the Linden neighborhood, which has experienced persistent poverty. Using the mobility energy productivity (MEP) metric to examine travel time, cost, and energy efficiency, we show current transit service is undesirable due to excessive travel time (70 min, MEP = 0), while driving alone (MEP = 0.20) may be less desirable than a hypothetical, fare-free microtransit service (MEP = 0.23). Updating MEP to use locally-derived input data can help identify parameters under which providing microtransit service in a specific place has compelling benefits in terms of vehicle energy efficiency as well as cost and travel time for riders.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Space Architecture: The Role, Work and Aptitude
Space architecture has been an emerging discipline for at least 40 years. Has it arrived? Is space architecture a legitimate vocation or an avocation? If it leads to a job, what do employers want? In 2002, NASA Headquarters created a management position for a space architect whose job was to "lead the development of strategic architectures and identify high level requirements for systems that will accomplish the Nation's space exploration vision." This is a good job description with responsibility at the right level in NASA, but unfortunately, the office was discontinued two years later. Even though there is no accredited academic program or professional licensing for space architecture, there is a community of practitioners. They are civil servants, contractors and academicians supporting International Space Station and space exploration programs. In various ways, space architects currently contribute to human spaceflight, but there is a way for the discipline to be more effective in developing solutions to large scale complex problems. This paper organizes contributions from engineers, architects and psychologists into recommendations on the role of space architects in the organization, the process of creating and selecting options, and intrinsic personality traits including why they must have a high tolerance for ambiguity.
Griffin, Brand↗
Is Knowledge about Running Applications Helping Improve Runtime Prediction of HPC Jobs?
High-performance computing systems rely upon scheduling algorithms to achieve high utilization. These schedulers rely upon user estimates of job resource requirements, such as runtime, to determine optimal scheduling of incoming jobs. These user estimates, however, are prone to error. To mitigate this error, significant research has been directed at providing better estimates of job runtime, usually employing machine learning techniques. These techniques are dependent upon the input features selected. Among the possible features is the primary application used by the job. In a survey of more than 20 papers directed at improving runtime prediction, only four included primary application as an input feature. We focus this investigation specifically on the value of adding primary application as an input feature, and find that it does improve model performance, especially for jobs with longer runtimes, though this improvement varies based on the application used. We recommend further research to determine the cause of this variability as well as an optimal strategy for employing a mixture of models both including and not including primary application as a feature.
MATHEMATICS AND COMPUTING↗
Is Knowledge About Running Applications Helping Improve Runtime Prediction of HPC Jobs?
High-performance computing systems rely upon scheduling algorithms to achieve high utilization. These schedulers rely upon user estimates of job resource requirements, such as runtime, to determine optimal scheduling of incoming jobs. These user estimates, however, are prone to error. To mitigate this error, significant research has been directed at providing better estimates of job runtime, usually employing machine learning techniques. These techniques are dependent upon the input features selected. Among the possible features is the primary application used by the job. In a survey of more than 20 papers directed at improving runtime prediction, only four included primary application as an input feature. We focus this investigation specifically on the value of adding primary application as an input feature, and find that it does improve model performance, especially for jobs with longer runtimes, though this improvement varies based on the application used. We recommend further research to determine the cause of this variability as well as an optimal strategy for employing a mixture of models both including and not including primary application as a feature.
feature selection↗
Education, Training and Career Pathway Opportunities for Buildings Energy Efficiency Programs Within the Corps Network
The Corps Network (TCN) is a national association that represents more than 150 local organizations around the country that work to provide job training and employment to individuals working on projects that provide community benefits. Through its partnership in the Better Buildings Workforce Accelerator, TCN requested technical assistance from the National Renewable Energy Laboratory (NREL) to support Corps organizations involved in – or interested in developing – programs related to energy efficiency in buildings. The goal of this project is to provide industry-recognized energy efficiency education/training models and resources that can be tailored and replicated by Corps across the country, and which can best prepare Corpsmembers to enter the energy efficiency workforce when they complete their terms of service.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing
Abstract We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Study Results on Knowledge Requirements for Entry-Level Airport Operations and Management Personnel
This paper identifies important topical knowledge areas required of individuals employed in airport operations and management positions. A total of 116 airport managers and airfield operations personnel responded to a survey that sought to identify the importance of various subject matter for entry level airport operations personnel. The results from this study add to the body of research on aviation management curriculum development and can be used to better develop university curriculum and supplemental training focused on airport management and operations. Recommendations are made for specialized airport courses within aviation management programs. Further, this study identifies for job seekers or individuals employed in entry level positions those knowledge requirements deemed important by airport managers and operations personnel at different sized airports.
Quilty, Stephen M.↗
Energy Community Atlas
The Energy Community Atlas provides efficient access to authoritative, curated, and relevant data that is vital to supporting energy planning, development, and economic growth across the U.S. In this effort, researchers at the National Energy Technology Laboratory (NETL) are utilizing advanced data visualization and transformation capabilities to develop an integrated, data atlas and resource focused on supporting energy community transitions to new manufacturing opportunities. Specifically, this project is working to find, acquire, integrate, and virtually host in a user-friendly, public and private solution from available resources, relevant to understanding and characterizing fossil energy communities themselves and inform energy planning, development, and economic growth opportunities, including opportunities for co-development to support manufacturing, critical materials, and more. This Atlas when complete is to offer a one-stop-shop for stakeholders to derive new insights to accelerate energy investments and strategic decision support needs. These are following datasets that are available as part of this ongoing project • Energy Community Atlas Map Package - This is ArcPro Map package and it contains all of the symbolized layers along with ArcPro map and geodatabase • Energy Community Atlas ArcGIS REST service - https://www.arcgis.com/apps/mapviewer/index.html?panel=gallery&suggestField=true&layers=537ced69bd88440380a62c2ec8aca30c • README Energy Community Atlas - Read me word document that has details about feature classes in Map package, ArcPro map and ArcGIS Rest Service
Bipartisan Infrastructure Law↗
The adult literacy evaluator: An intelligent computer-aided training system for diagnosing adult illiterates
An important part of NASA's mission involves the secondary application of its technologies in the public and private sectors. One current application being developed is The Adult Literacy Evaluator, a simulation-based diagnostic tool designed to assess the operant literacy abilities of adults having difficulties in learning to read and write. Using ICAT system technology in addition to speech recognition, closed-captioned television (CCTV), live video and other state-of-the art graphics and storage capabilities, this project attempts to overcome the negative effects of adult literacy assessment by allowing the client to interact with an intelligent computer system which simulates real-life literacy activities and materials and which measures literacy performance in the actual context of its use. The specific objectives of the project are as follows: (1) To develop a simulation-based diagnostic tool to assess adults' prior knowledge about reading and writing processes in actual contexts of application; (2) to provide a profile of readers' strengths and weaknesses; and (3) to suggest instructional strategies and materials which can be used as a beginning point for remediation. In the first and developmental phase of the project, descriptions of literacy events and environments are being written and functional literacy documents analyzed for their components. Examples of literacy events and situations being considered included interactions with environmental print (e.g., billboards, street signs, commercial marquees, storefront logos, etc.), functional literacy materials (e.g., newspapers, magazines, telephone books, bills, receipts, etc.) and employment related communication (i.e., job descriptions, application forms, technical manuals, memorandums, newsletters, etc.). Each of these situations and materials is being analyzed for its literacy requirements in terms of written display (i.e., knowledge of printed forms and conventions), meaning demands (i.e., comprehension and word knowledge) and social situation. From these descriptions, scripts are being generated which define the interaction between the student, an on-screen guide and the simulated literacy environment. The proposed outcome of the Evaluator is a diagnostic profile which will present broad classifications of literacy behaviors across the major areas of metacognitive abilities, word recognition, vocabulary knowledge, comprehension and writing. From these classifications, suggestions for materials and strategies for instruction with which to begin corrective action will be made. The focus of the Literacy Evaluator will be essentially to provide an expert diagnosis and an interpretation of that assessment which then can be used by a human tutor to further design and individualize a remedial program as needed through the use of an authoring system.
Yaden, David B., Jr.↗
Quantifying Uncertainty in HPC Job Queue Time Predictions
High Performance Computing (HPC) has developed at an unprecedented pace in recent decades. This growth has demanded corresponding development in the area of HPC Operational Data Analytics (ODA), which encompasses a wide range of data analysis techniques, ML/AI efforts, tools, and visualizations. Published studies in ODA offer a variety of practical ways to inform HPC users, administrators, procurement managers, and other stakeholders. Uncertainty analysis, however, is rare in the related published literature. For instance, we identify only 1 out of 14 existing studies focused on job queue time prediction that investigates the uncertainty aspect of their proposed predictions. We recognize the utmost importance uncertainty quantification can have in such predictive analytics solutions, with consequences in how users interpret information they receive, and attempt to bridge this gap. With the goal of improving access to such insights, we develop a process for determining upper and lower bounds of the predicted queue times of a regression model at a specified confidence level. Our current research is focused on the uncertainty in predicting job queue times, yet our approach may be employed in predicting other metrics.
HPC↗
An analysis of job placement patterns of black and non-black male and female undergraduates at the University of Virginia and Hampton Institute
Research questions were proposed to determine the relationship between independent variables (race, sex, and institution attended) and dependent variables (number of job offers received, salary received, and willingness to recommend source of employer contact). The control variables were academic major, grade point average, placement registration, nonemployment activity, employer, and source of employer contact. An analysis of the results revealed no statistical significance of the institution attended as a predictor of job offers or salary, although significant relationships were found between race and sex and number of job offers received. It was found that academic major, grade point average, and source of employer contact were more useful than race in the prediction of salary. Sex and nonemployment activity were found to be the most important variables in the model. The analysis also indicated that Black students received more job offers than non-Black students.
Anderson, A. F.↗
An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer
Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.
Clifford↗
A Supply Chain Road Map for Offshore Wind Energy in the United States
"A Supply Chain Road Map for Offshore Wind Energy in the United States" identifies pathways to developing a domestic offshore wind supply chain that can manufacture and deploy the major components needed to set the United States on a pathway to installing 30 GW of offshore wind by 2030 and 110 GW by 2050. The report estimates that this supply chain could require an investment of at least $\$$22.7 billion this decade to meet an annual demand for components, ports, and vessels in 2030. Although this is a considerable investment, it could allow the industry to install around $\$$100 billion worth of offshore wind this decade by reducing risk of delays due to global supply chain bottlenecks and creating a robust network of assets that will continue to be effective well beyond 2030. The United States would need at least 34 manufacturing facilities employing 10,000 workers, 39,000 jobs in the supporting supply chain, 10 marshaling ports, 4-6 dedicated wind turbine installation vessels, 4-6 dedicated heavy-lift vessels, and 4-8 U.S.-flagged specialized feeder barges to come online this decade to support an average annual deployment of 4-6 gigawatts offshore wind capacity per year. This supply chain could be developed in 6-9 years, but would require near-term decision making and efficient permitting and planning to strategically develop these resources by 2030. Additional investment and expansion would be required in the 2030s as the sector expands into new regions (such as the Gulf of Mexico) and new technologies (such as larger wind turbines and floating wind energy projects). Furthermore, the planning process needs to meaningfully engage with communities that will be impacted by supply chain expansion to achieve just outcomes and maximize benefits to these stakeholders, which will result in a more equitable and sustainable supply chain. While U.S. offshore wind has made significant progress in recent years, remaining supply chain challenges include uncertainty surrounding deployment and procurement timelines; a lack of port and vessel infrastructure; and limitations in the available workforce, supporting supplier networks, and energy justice best practices. However, many of these problems can be addressed through improved communication between key stakeholder groups, support from federal and state governments, and forward-thinking designs of supply chain assets to accommodate future technology changes for fixed-bottom and floating offshore wind. Although it is a significant task, developing these domestic capabilities represents a once-in-a-generation opportunity to contribute to a decarbonized energy future and also create massive economic benefits that are distributed throughout the country.
17 WIND ENERGY↗
Strategies and Approaches for Developing Hands-On Training for Cold Climate Heat Pumps
The International Center for Appropriate and Sustainable Technology (ICAST) is in the process of implementing a program funded by the US Department of Energy (DOE) in which they are providing cold climate heat pump (CCHP) curriculum and training to HVAC workers, ranging from entry to experienced levels. They have coordinated with Santa Fe Community College (SFCC) to develop online curricula, and through their involvement with the DOE Better Buildings Workforce Accelerator, they requested technical assistance from the National Renewable Energy Laboratory (NREL) to help them develop programs that incorporate hands-on and on-the-job skills training and job placement services in coordination with local employers. This report offers a step-by step-overview of the process for developing a new workforce development and hands-on training program in a new region, outlining practices to help understand the market, and to effectively recruit, train, and connect people to HVAC jobs installing cold climate heat pumps.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Americans with Disabilities Act considerations for the practice of occupational medicine
The Americans with Disabilities Act (ADA), although developed in the context of civil rights legislation, is likely to have notable impact on the practice of occupational medicine. The ADA contains provisions limiting the use of preplacement examinations to determinations of the capability to perform the essential functions of the job and of direct threat to the health and safety of the job applicant and others. The Title 1 employment provisions of the ADA established definitions and requirements similar to those found in section 504 of the Rehabilitation Act of 1973, as amended; leading cases that have been litigated under the Rehabilitation Act, as amended, are described. The limitations of available scientific and medical information related to determinations of job capability and direct threat and ramifications of the ADA on the practice of occupational medicine are discussed.
St.clair, Steven↗