SEARCH · Engineering Papers

Results for “research efforts”

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 1,081 records · Page 60

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Recent advances in metallographic polishing for SRF application

This paper is an overview of the metallographic polishing R\&D program covering Niobium and Copper substrates treatment for thin film coating as an alternative fabrication pathway for 1.3 GHz elliptical cavities. The presented research is the result of a collaborative effort between IJCLab, CEA/Irfu, HZB, and KEK in order to develop innovative surface processing and cavity fabrication protocols capable of meeting stringent requirements for SRF surfaces, including the reduction of safety risks and ecological footprint, enhancing reliability, improving the surface roughness, and potentially allowing cost reduction. The research findings will be disclosed.

Hryhorenko, O.↗

DOE OSTI2023

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2022 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office (BETO). It allows for the impact of research progress (both directly achieved in-house at the National Renewable Energy Laboratory [NREL] and furnished by partner organizations) to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked toward out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae SOT benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted primarily under NREL research and development projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model. Through partnerships under DISCOVR, collaborators at ASU furnished details on cultivation performance metrics including biomass productivity and harvest densities for recent growth trials done at the AzCATI site. The resulting biomass productivity was calculated at 18.5 g/m2/day (ash-free dry weight [AFDW], annual average) for seasonal cultivation of Picochlorum celeri, Tetraselmis striata LANL1001, and Monoraphidium minutum 26B-AM biomass strains at the ASU site. Picochlorum celeri achieved the best productivity from May to September, with Monoraphidium minutum 26B-AM being used in October, November, March, and April, and Tetraselmis striata employed during winter months (December through February). Beyond the standard SOT models, in Appendix C of this report we also present an industry case study evaluating several scenarios reflective of outdoor cultivation data furnished by an industry collaborator. This case study provides a supplementary datapoint on work being performed elsewhere achieving comparable cultivation productivity with more favorable compositional quality, producing biomass enriched in lipids as may be more optimal for conversion upgrading to fuels and products.

09 BIOMASS FUELS↗

DOE OSTI2024

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2023 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office (BETO). It allows for the impact of research progress (both directly achieved in-house at the National Renewable Energy Laboratory [NREL] and furnished by partner organizations) to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked toward out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae SOT benchmarking efforts historically focused both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted primarily under NREL research and development projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model. Through partnerships under DISCOVR, collaborators at ASU furnished details on cultivation performance metrics including biomass productivity and harvest densities for recent growth trials done at the AzCATI site. The resulting biomass productivity was calculated at 16.7 g/m 2 /day (ash-free dry weight [AFDW], annual average) for seasonal cultivation of Picochlorum celeri TG2 and Monoraphidium minutum 26B-AM biomass strains at the ASU site. Picochlorum celeri achieved the best productivity from April to September, with Monoraphidium minutum 26B-AM being used between October and March. Tetraselmis striata LANL1001, usually part of the strain rotation in previous cultivation SOTs, was supplanted by Monoraphidium minutum 26B-AM in this year's outdoor cultivation trials. Finally, building from an industry case study presented in the 2022 SOT report, in the Appendix of this report we provide an update on further improved data furnished by an industry collaborator and resultant impacts on economics reflecting several seasonal scenarios. This case study provides a supplementary datapoint on work being performed elsewhere with a more dedicated focus on improved compositional quality, producing biomass enriched in lipids as may be more optimal for conversion upgrading to fuels and products.

09 BIOMASS FUELS↗

DOE OSTI2020

Predicting Future Disease Burden in a Rapidly Changing Climate

The interplay of a rapidly changing climate and infectious disease occurrence is emerging as a critical topic, requiring investigation of possible direct, as well as indirect, connections between disease processes and climate-related variation and phenomena. First, we introduce and overview three infectious disease exemplars (dengue, influenza, valley fever) representing different transmission classes (insect-vectored, human-to-human, environmentally-transmitted) to illuminate the complex and significant interplay between climate disease processes, as well as to motivate discussion of how Sandia can transform the field, and change our understanding of climate-driven infectious disease spread. We also review state-of-the-art epidemiological and climate modeling approaches, together with data analytics and machine learning methods, potentially relevant to climate and infectious disease studies. We synthesize the modeling and disease exemplars information, suggesting initial avenues for research and development (R&D) in this area, and propose potential sponsors for this work. Whether directly or indirectly, it is certain that a rapidly changing climate will alter global disease burden. The trajectory of climate change is an important control on this burden, from local, to regional and global scales. The efforts proposed herein respond to the National Research Councils call for the creation of a multidisciplinary institute that would address critical aspects of these interlocking, cascading crises.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Leafweb: Leaf Gas Exchange and Pulse-Amplitude Modulated Fluorometry for C4 Species, June 2026 Release

This dataset contains leaf gas exchange and Pulse-Amplitude Modulated (PAM) fluorometry for 98 C4 species. The C4 photosynthetic pathway employs specialized CO2 concentration mechanisms and Kranz anatomy to enrich CO2 concentration around Rubisco, the enzyme that catalyzes carbon fixation in the Calvin-Benson cycle to suppress photorespiration and increase the use efficiencies of light, nitrogen, and water as compared to the C3 photosynthetic pathways. Large-scale C4 photosynthetic datasets are relatively scarce, which has affected C4 photosynthesis research. To improve C4 photosynthetic data availability, Leafweb organized an effort to systematically collect, compile, standardize, and organize measurements of leaf gas exchange and/or Pulse-Amplitude Modulated (PAM) fluorometry of C4 species. This derived a C4 photosynthetic dataset containing measurements made by independent researchers in multiple countries in various environments (field, garden, or greenhouse). It covers three biochemical subtypes – the nicotinamide adenine dinucleotide phosphate-malic enzyme (NADP-ME), nicotinamide adenine dinucleotide-malic enzyme (NAD-ME), and phosphoenolpyruvate carboxykinase (PEP-CK) subtypes. This dataset is useful for using Artificial Intelligence / Machine Learning and mechanistic models to study C4 photosynthesis and compare across different biochemical subtypes. This dataset contains 3 compressed (*.zip) folders containing 1,892 data files in comma-separate values (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Zhou, Haoran [Tianjin University, China]↗

DOE OSTI2020

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Preliminary Regional Assessment of Potential Storage Complexes, Including Capacities and Costs, Based on Application of NRAP and SCO2T (Deliverable 3.3) Storage Complexes

The Recipient will assist with the field validation of one or more risk assessment toolsets through: 1) collaborative research; 2) sharing of relevant datasets, information, and technical insights from field efforts; and 3) other modeling and simulation toolsets as they are developed. Collaborative research could include, but is not limited to: 1) demonstrating use of field data for improved leakage pathway characterization, uncertainty reduction, and risk management and uncertainty workflows; 2) testing and validation of a specific National Risk Assessment Partnership (NRAP) tool using site specific data; and 3) improved modeling or reduced-order modeling of geophysical monitoring.

42 ENGINEERING↗

DOE OSTI2023

Combinatoric Researchers at Sandia National Laboratories: An ethnographic study

Combinatorial research, the incorporation of multiple domains in a unified research agenda, is a strong contributor to the growing corpus of scientific knowledge and technological advancements worldwide. In 2019, a study team at Sandia National Laboratories (Sandia, the Labs) used a systems approach to understand if and how combinatorial research agendas were playing out at Sandia, one of America’s premiere national security research venues. The study team used the data collection effort described in this report to ground the discussion of the broad social environment and particular organizational environments within which combinatorial research agendas are developed, as described in the full study. The team interviewed twenty-five staff members engaged in combinatorial research at Sandia in New Mexico and California during the months of June – September 2019. Analysis of this corpus of ethnographic data, combined with knowledge drawn from relevant literature, concluded that there is an individual type who would be most likely to engage in combinatoric research, described by both demographic and psychographic components. This type demonstrates both intellectual depth and the curiosity which leads to breadth. The analysis also showed that Sandia as an organization and as perceived by the respondents, set up tension for the combinatorial researcher. While Sandia was generally agnostic towards combinatorial research, that agnostic posture depended on whether the researcher was able to fulfill all her customer obligations – obligations that are structured primarily in transactional relationships with customers with relatively short time horizons. This report concludes with suggestions for additional research in the ethnographic domain.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Port Authority of New York and New Jersey (PANYNJ) Distributed Energy Resource (DER) Techno-Economic Comparison: Cooperative Research and Development (Final Report)

To support NYPA's efforts in delivering a feasibility study to advise PANYNJ on future distributed energy resource (DER) deployments at their facilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

The Quantum Nature and Mass of the Neutrino. FY20 Annual Laboratory Continuation Progress Report

Over the last 100 years we have learned a much about the neutrino, but there remain interesting questions about this weakly interacting particle. In particular, at LLNL we are developing experiments to measure the mass and the quantum nature of the neutrino. The 2015 long range plan recommended tonne-scale neutrinoless double beta decay experiments as the top new project priority and this experiment will target the quantum nature of the neutrino. The LLNL team is motivated and focused on developing the best technology for this experiment which is a liquid xenon time project chamber called nEXO. On a longer time scale, LLNL is also developing technology to measure the neutrino mass with tritium decay experiments. Work on nEXO at LLNL started in 2015 with an LDRD and program development funds to develop the nEXO concept, publish sensitivity predictions, explore alternatives and risks, and to build a credible project team and this effort is on going. In addition, we received research funding from DOE-SC NP and LLNL manages pre-conceptual R&D for the nEXO collaboration a portion of which is executed at LLNL. The Project 8 effort is solely funded by LLNL LDRD, and ends this year. A second LDRD effort is focused on repurposing cyclotron radiation emission spectroscopy for eV-scale X-ray detection. This second effort, while separated from Project 8, still has scientific and technical commonalities with Project 8. The funding for this X-ray detection effort will continue for one more year. LLNL has a long history of building large projects, science projects and time projection chambers, but nEXO is in fact the first project of this scale that LLNL is prepared to lead for DOE-SC NP.We have the tools, skills, people and motivation to make nEXO a reality. The current program development dollars are used to prepare the nEXO concept for down select and CD1. These internal LLNL dollars pay for a number of things including project staff to organize the nEXO collaboration for the various reviews that lie ahead, to develop the draft plans and structure to manage the project as well as setting up an external advisory committee. The current LDRD is exploring alternatives that effect the risk profile as well as possible performance improvements. The DOE-SC NP base funding is targeted at simulation and analysis of the nEXO concept in preparation for the down select and refinement of the understanding of the detector as well as scientific effort on the large xenon test stand (LXTS) that will burn down one of the largest risks to the nEXO project. Lastly, LLNL is leading the pre-conceptual R&D effort and managing the funds for the nEXO collaboration. The results of this effort are reported elsewhere, but the scope of this executed at LLNL will be reported here and is primarily the engineering and construction of the LXTS experiment. The primary technical contribution of LLNL to the Project 8 concept is the formation and study of atomic tritium. Atomic tritium is necessary for Project 8 to reach the ultimate sensitivity. LLNL has considerable experience with tritium and is well suited for this crucial work. Although the focus of this work is strictly fundamental science, there has already been one significant spinoff to develop a new means to measure radio xenon in the air

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Earth System Model Development - Energy Exascale Earth System Model (2020 Principal Investigator Meeting Report)

As part of the U.S. Department of Energy (DOE) Office of Biological and Environmental Research (BER), the Earth System Model Development (ESMD) program area supports significant research in Earth system model development, including major efforts in the Energy Exascale Earth System Model (E3SM) project. Convened virtually on October 26–29, the 2020 ESMD-E3SM Principal Investigator (PI) Meeting provided a forum to survey ESMD sponsored research, recent progress made by the ESMD science team and the broader Earth system modeling community within and outside of DOE, foster interactions across ESMD projects, and discuss research gaps and opportunities for future advancements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Understanding Costs Associated with Wind Energy Opposition and Stakeholder Engagement

Wind energy social science research historically focused on the social acceptance of wind energy development. Research in this field is robust, and scholars have identified drivers influencing attitudes and acceptance. The criteria defining the opposition of wind energy, and their costs, although related, are less well understood. This gap in research includes the costs of delayed and failed projects to communities and developers. The International Energy Agency (IEA) Wind Task 28 - The Social Science of Wind Energy Acceptance outlined a work package to help answer that question. The first deliverable for IEA Wind Task 28, Work Package 2, was an annotated bibliography that identified key pieces of literature that quantify the costs of opposition to wind projects. Although there is a robust wind social acceptance literature, our efforts highlighted that there has been little research directly quantifying the cost of opposition, engagement, delays, and failures. To directly summarize the appropriate literature and provide context for potential future work, the literature review ranged from directly relevant articles to works providing context and valuable information for our research objective in the future. This associated deliverable, a briefing document summarizing the outcomes of our literature search, is meant to guide future research on opposition to wind energy for IEA Task 28 and beyond.

opposition↗

DOE OSTI2023

How to engineer the unknown: Advancing a quantitative and predictive understanding of plant and soil biology to address climate change

Our basic understanding of carbon cycling in the biosphere remains qualitative and incomplete, precluding our ability to effectively engineer novel solutions to climate change. How can we attempt to engineer the unknown? This challenge has been faced before in plant biology, providing a roadmap to guide future efforts. We use examples from over a century of photosynthesis research to illustrate the key principles that will set future plant engineering on a solid footing, namely, an effort to identify the key control variables, quantify the effects of systematically tuning these variables, and use theory to account for these observations. The main contributions of plant synthetic biology will stem not from delivering desired genotypes but from enabling the kind of predictive understanding necessary to rationally design these genotypes in the first place. Only then will synthetic plant biology be able to live up to its promise.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Enabling a Physical Twin for Control Methods Evaluation

Advanced nuclear reactors play an important role in the energy future of the United States and the rest of the world. They are designed and operated based on a different model than that of the current operating fleet, thus enabling deployment in remote locations and allowing for safe semi-autonomous or autonomous operations. Such characteristics require the development of a new reactor control paradigm. A significant factor in the development of control technologies and methods is integration of the various technologies and methods with each other and with hardware (both reactor system hardware and control hardware). A recent workshop on control of advanced reactors identified the lack of a flexible, expandable software/hardware infrastructure to enable such integration as a key gap. A previous phase of the current effort involved developing and demonstrating the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) platform, which is capable of integrating autonomous-control-enabling technologies and methods, without the constraints imposed by existing software solutions. This platform will enable advanced reactor developers to deploy and test any developed technologies and methods by employing a common framework, and to couple them with their own models and hardware. The present phase of this effort entails using the Microreactor Automated Control System (MACS) platform, which was developed by the U.S. Department of Energy (DOE) Microreactor Program, to serve as a control method testbed. MACS can be used by advanced reactor developers to integrate their control related research activities with any reactor system. For the present effort, MACS was customized to mirror Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and COMMAND was leveraged to enable MACS to emulate the physics of MARVEL, thus positioning MACS as a physical twin of MARVEL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Understanding the Gap between Academic Research and Industrial Requirements in Rechargeable Zinc-Ion Batteries

Rechargeable Zn-ion batteries (RZIBs) are considered to be promising energy storage systems for large-scale applications owing to their relatively high energy densities and inherently low costs, environmental benignity, as well as safety. With increasing interest and effort being devoted to this field, RZIBs are being tremendously advanced and are very likely to be commercialized in the near future. However, some challenges remain that need to be addressed. Moreover, reported results are quite often overstated through artificial exaggeration and cannot be translated to industrial applications as they were obtained under ideal testing conditions. Therefore, in this perspective, here we discuss key parameters that need to be carefully considered when translating laboratory-developed RZIBs into commercial reality. We also present a critical mini-review on RZIBs and devote effort to issues that are overlooked in academic research. We believe that this perspective provides new or seldom-discussed insight for future work and bridges the gap between academia and industry.

25 ENERGY STORAGE↗

DOE OSTI2021

Overview of the Second Workshop on Scholarly Document Processing

With the ever-increasing pace of research and high volume of scholarly communication, scholars face a daunting task. Not only must they keep up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. These needs have motivated an increasing focus on computational methods for enhancing search, summarization, and analysis of scholarly documents. However, the various strands of research on scholarly document processing remain fragmented. To reach out to the broader NLP and AI/ML community, pool distributed efforts in this area, and enable shared access to published research, we held the 2nd Workshop on Scholarly Document Processing (SDP) at NAACL 2021 as a virtual event (https://sdproc.org/2021/). The SDP workshop consisted of a research track, three invited talks, and three Shared Tasks (LongSumm 2021, SCIVER, and 3C). The program was geared towards the application of NLP, information retrieval, and data mining for scholarly documents, with an emphasis on identifying and providing solutions to open challenges.

Beltagy, Iz↗