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At least 361 records · Page 20

Modeling Guidelines for Code Generation in the Railway Signaling Context

Modeling guidelines constitute one of the fundamental cornerstones for Model Based Development. Their relevance is essential when dealing with code generation in the safety-critical domain. This article presents the experience of a railway signaling systems manufacturer on this issue. Introduction of Model-Based Development (MBD) and code generation in the industrial safety-critical sector created a crucial paradigm shift in the development process of dependable systems. While traditional software development focuses on the code, with MBD practices the focus shifts to model abstractions. The change has fundamental implications for safety-critical systems, which still need to guarantee a high degree of confidence also at code level. Usage of the Simulink/Stateflow platform for modeling, which is a de facto standard in control software development, does not ensure by itself production of high-quality dependable code. This issue has been addressed by companies through the definition of modeling rules imposing restrictions on the usage of design tools components, in order to enable production of qualified code. The MAAB Control Algorithm Modeling Guidelines (MathWorks Automotive Advisory Board)[3] is a well established set of publicly available rules for modeling with Simulink/Stateflow. This set of recommendations has been developed by a group of OEMs and suppliers of the automotive sector with the objective of enforcing and easing the usage of the MathWorks tools within the automotive industry. The guidelines have been published in 2001 and afterwords revisited in 2007 in order to integrate some additional rules developed by the Japanese division of MAAB [5]. The scope of the current edition of the guidelines ranges from model maintainability and readability to code generation issues. The rules are conceived as a reference baseline and therefore they need to be tailored to comply with the characteristics of each industrial context. Customization of these recommendations has been performed for the automotive control systems domain in order to enforce code generation [7]. The MAAB guidelines have been found profitable also in the aerospace/avionics sector [1] and they have been adopted by the MathWorks Aerospace Leadership Council (MALC). General Electric Transportation Systems (GETS) is a well known railway signaling systems manufacturer leading in Automatic Train Protection (ATP) systems technology. Inside an effort of adopting formal methods within its own development process, GETS decided to introduce system modeling by means of the MathWorks tools [2], and in 2008 chose to move to code generation. This article reports the experience performed by GETS in developing its own modeling standard through customizing the MAAB rules for the railway signaling domain and shows the result of this experience with a successful product development story.

Ferrari, Alessio↗

Innovation at the Edge of Space- An Engine for Global Opportunities

Microgravity based commercial opportunities are broad, with applications ranging from fiber optics, device-grade semiconductor crystals, space beads, new materials, cells microencapsulation, 3D tissues and cell cultures, genetic and molecular changes of immune suppression, protein and virus crystal growth, perfume and hair care. To date, primarily the knowledge gained from observing and understanding new end states of systems unraveled in microgravity has been translated into unique technologies and business opportunities on Earth. In some instances existing flight qualified hardware is immediately available for commercial RD for small-scale in-space manufacturing. Overall, products manufactured in microgravity have key properties usually surpassing the best terrestrial counterparts. Commercially, these products have an attractive touch of space which aids in marketing.The talk will addresses the potential benefits of microgravity research for a variety of terrestrial markets by (1) surveying the level of awareness and interest of parties from different commercial sectors (2) assessing the potential of microgravity to stimulate innovation in future product development and (3) formulating a synergistic strategy to use microgravity for economic growth and public benefit.Our findings originating primarily from discussions with 100+ non-aerospace private companies among the high-tech Silicon Valley ecosystem, show that the opportunities and benefits of using the ISS are largely not considered by experts, primarily due to a lack of awareness of the breadth of terrestrial applications that have been enabled or enhanced by microgravity RD. Based on this dialogue, the concept of microgravity verticals is developed to translate the benefits of the microgravity environment into blue ocean business opportunities for various key US commercial sectors.

orbital economy↗

Defining and Measuring Forest Dependence in the United States: Operationalization and Sensitivity Analysis

This manuscript helps bridge a gap between theoretical work that advocates for a broad view of forest dependence, and empirical work that has focused narrowly on economic measures. Background: Forest dependence has been widely recognized as a valuable concept for understanding human communities’ well-being and vulnerability to shocks and changes. Past theoretical literature has highlighted the importance of recognizing various types of dependence—environmental, economic, and social—yet past empirical literature on the topic in the United States has almost exclusively relied on measures of economic dependence such as employment and earnings from the traditional forest products sector. Objective and Methods: As a first step to bridge the gap between the theoretical and empirical, we reviewed the existing, publicly available, reliable, wall-to-wall data sources to identify alternate proxy measures for forest dependence. Data availability made the analysis feasible only at the county level—the administrative subdivisions of the state—or higher. Results and Conclusions: We created environmental, economic, and social criteria based on threshold levels of the following proxy variables: forest area, earnings, employment, and indigenous population. Using these criteria, we identified 524 counties to be potentially forest-dependent of 3140 total counties in the United States. The largest concentration was in the Pacific Northwest and Southeast regions, and a higher proportion were non-metro counties than metro. Varying the threshold levels significantly changes the number of counties identified but does not alter the overall geographic trends.

54 ENVIRONMENTAL SCIENCES↗

The changing tide: Federal support of civilian-sector R and D

The involvement of the Federal government in civilian sector research and development is discussed. Relevant policies are put in an historical perspective. The roles played by industrial research and public funding are reveiwed. Government support of basic an generic research, clientele-oriented applied research, and research with commercial ends is studied. Procurement, anti-trust, and patent policies, all of which affect the climate for private research and development, are examined.

Fusfeld, H. I.↗

Advancing Open Source Science Initiatives Through Public-Private Partnerships

Collaboration is fundamental to advancing open science within the science community. With the recent developments in technology and research, the establishment of formal partnerships between the private sector and government agencies are needed to bridge the knowledge gaps and expedite the time to actionable science. NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT) seeks to address this challenge by establishing non-reimbursable Space Act Agreements with industry leaders in cloud computing, artificial intelligence (AI) and machine learning. The purpose of these agreements is to advance open source science initiatives in the areas of data discovery, access and use of high value NASA science data sets on the cloud. As well as, jointly work on common research problems to accelerate the development and adoption of new AI technologies. Current success stories include co-locating NASA datasets from multiple science disciplines on one platform using Amazon Web Services Open Data Registry, developing AI Foundation Models for Science with IBM and co-hosting training workshops and tutorials for the science community aimed at providing hands-on experience with using NASA data and AI models on the cloud. In summary, we will present an overview of our partnerships supporting open source science initiatives, describe current activities and lessons learned that may be useful to others considering similar partnerships with the private sector.

Elizabeth Fancher↗

H2@Scale CRADA: CA Research Consort. (Ref. Station, Fueling Perf. Test Device, Station Cap Model)

Heavy-duty (HD) hydrogen stations are an essential part of building a clean energy infrastructure by lowering greenhouse gas emissions and criteria pollutants from the trucking industry. Clean fuel at HD stations also supports energy, environmental, and social justice by preventing pollution near the stations and on truck routes while strengthening U.S. manufacturing and providing pathways to private sector uptake. The goal of the CA Research Consortium is to continue the research partnership between national laboratories, DOE, and California public agencies for the advancement of hydrogen fueling infrastructure for HD vehicles. This cooperative work directly impacts California's transition to Zero Emission Trucks and will provide tools and information that lead to more efficient design, acceptance, and commissioning of these larger capacity, higher flow rate stations serving HD hydrogen trucks such as class 8 trucks in long haul applications.

AMR↗

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 59: Japanese Technological Innovation. Implications for Large Commercial Aircraft and Knowledge Diffusion

This paper explores three factors-public policy, the Japanese (national) innovation system, and knowledge-that influence technological innovation in Japan. To establish a context for the paper, we examine Japanese culture and the U.S. and Japanese patent systems in the background section. A brief history of the Japanese aircraft industry as a source of knowledge and technology for other industries is presented. Japanese and U.S. alliances and linkages in three sectors-biotechnology, semiconductors, and large commercial aircraft (LCA)-and the importation, absorption, and diffusion of knowledge and technology are examined next. The paper closes with implications for diffusing knowledge and technology, U.S. public policy, and LCA.

Pinelli, Thomas E.↗

Exploring New Ways to Classify Industries for Energy Analysis and Modeling

As the US moves closer to embracing a net zero greenhouse gas emissions position, combustion processes outside the power sector are becoming urgent concerns. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning that even a single product group can vary broadly in its production routes and associated energy usage. In the US, the North American Industry Classification System (NAICS) serves as the basis for data collection and reporting. In turn, data based on NAICS is the foundation of most US energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for plans to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data to build more detail into heterogeneous sectors is scarce. This work explores alternative classification schemes for industry based on energy use characteristics, and provides a validation of an approach to make facility-level energy use estimates based on publicly available data from the greenhouse gas reporting program. First, several approaches to industrial taxonomies and their usefulness for industrial energy modeling are summarized. Data from Industrial Assessment Centers is analyzed using unsupervised machine learning techniques to detect clusters. Cladistics, an approach from biology, is adapted to energy and process characteristics of industries. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation. Finally, validation is performed for facility-level energy estimates from the US EPA Greenhouse Gas Reporting Program. This validation assists in making this data source available for use in energy modeling. Together, this work explores alternative approaches for categorizing industries in a way that aids understanding energy use, and presenting pathways for the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assessing outdoor air quality and public health impact attributable to residential black carbon emissions in rural China

Black carbon (BC) is a significant component of particulate matter (PM) that relates to air pollution, climate forcing, and further implications for public health. BC is predominantly released from the combustion of solid fuels. Combustion of low-quality fuels in rural China may induce severe respiratory and cardiopulmonary health outcomes for residents, which have however been inadequately assessed. One major reason for the limited understanding is the lack of a high-resolution inventory. An improved method of estimating the BC-associated public health burden is needed. This work quantified premature mortalities due to residential BC emissions in rural China. Domestic BC emissions at 1×1 km resolution were compiled based on previous field investigation, which were further configured for air quality simulation. A chemistry transport model, WRF–CMAQ v5.2, was employed for simulating BC concentrations. The consequent premature mortalities were quantified by a BC-specific concentration-response function (CRF) derived from an epidemiological study. Results show that residential combustion of solid fuel in rural China emitted 648.0 Gg (95%CI: 361.0–965.9) BC in 2014, after dispersion, accounting for 51.8% of annual mean ground-level BC concentration in China. Such impact was most severe in North and Northeast China, and the Sichuan Basin. The further investigation estimated 171,000 (95%CI: 69,000–387,000) premature mortalities that were attributable to exposure to rural residential BC. These findings reveal the major contribution of rural residential BC emissions to air pollution formation and public health impacts. Our findings are anticipated to provide useful information for enacting the next-stage environmental strategy for the residential sector in China.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

PR100: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy [Slides]

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050. The PR100: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy study, led by the National Renewable Energy Laboratory (NREL), will leverage world-class expertise, cross-sector modeling capabilities, and community engagement to generate feasible pathways to affordable and reliable electricity across the archipelago. PR100 is being funded by the Federal Emergency Management Agency through an interagency agreement with DOE's Office of Electricity to support recovery efforts in the island's energy sector leveraging the expertise and capabilities of the National Laboratories including Argonne, Lawrence Berkeley, NREL, Oak Ridge, Pacific Northwest, and Sandia. The public is invited to this virtual launch event to learn more about the scope and benefits of the study and opportunities for engagement. Welcoming remarks will be provided by Jennifer M. Granholm, Secretary of the U.S. Department of Energy; Martin Keller, Director of the National Renewable Energy Laboratory; and Deanne Criswell, Administrator of the Federal Emergency Management Agency.

100% renewable energy↗

An Assessment of the Effectiveness of the AGATE Program Management Model

This report describes the collaborative program model chosen to implement an aeronautics research and technology program from 1994 through 2001: the Advanced General Aviation Transport Experiments (AGATE) Program. The Program had one primary objective: to improve the ability of the General Aviation industry to adopt technology as a solution to fulfill public benefit objectives. The primary objective of this report is to assess the program s ability to meet a combination of "effectiveness measures" from multiple stakeholders. The "effectiveness" of any model forms the foundation of legitimate questions for policy makers and professional federal managers. The participants rated AGATE as achieving its primary objectives and rating well on effectiveness in most areas, with high measures for relevance, cost, speed and public benefit, but lower measures for institutional fit and flexibility at dealing with the larger NASA organizational structure. This pattern mirrors private sector surveys and represents a tradeoff between the benefits of tailoring a program using partnering, versus the changes necessary within the institutional structure to support such tailoring.

Warner, Timothy P.↗

Modeling Freight Traffic Demand and Highway Networks for Hydrogen Fueling Station Planning: A Case Study of U.S. Interstate 75 Corridor

The use of hydrogen as an alternative transportation fuel has gained much interest in recent years. Hydrogen can be utilized in electric vehicles equipped with hydrogen powertrains (including hydrogen internal combustion engines or fuel cells). Given that most of the freight in the U.S. is transported via diesel trucks, transition to hydrogen fuel would help achieve significant environmental benefits as well as accelerate the decarbonization of the freight transportation sector. This paper presents the methodology and results of a case study on modeling freight traffic demand and highway networks based on publicly available data for the Interstate 75 freight corridor. The purpose of this study is to prepare input traffic and network data that can support the planning of a hydrogen fueling station infrastructure. In particular, the data can be used for siting and characterizing an optimized framework of hydrogen fueling stations from candidate diesel stations along the Interstate 75 corridor. The methodologies developed and presented in this paper may be readily expanded and applied to any transport corridor given the data availability. This paper is the first in a series that will build out a comprehensive model to optimize a consolidated national hydrogen refueling infrastructure eco-system targeted at commercial vehicles.

Uddin, Majbah↗

Spinoff 2007

In accordance with congressional mandates cited in the National Aeronautics and Space Act of 1958 and the Technology Utilization Act of 1962, NASA was directed to encourage greater use of the Agency's knowledge by providing a link between the NASA research community and those who might use the research for commercial or industrial products. For more than 40 years, NASA has nurtured partnerships with the private sector to facilitate the transfer of NASA-developed technologies. The benefits of these partnerships have reached throughout the economy and around the globe, as the resulting commercial products contributed to the development of services and technologies in the fields of health and medicine, transportation, public safety, consumer goods, environmental resources, computer technology, and industry. Since 1976, NASA Spinoff has profiled more than 1,500 of the most compelling of these technologies, annually highlighting the best and brightest of partnerships and innovations. Building on this dynamic history, NASA partnerships with the private sector continue to seek avenues by which technological achievements and innovations gleaned among the stars can be brought down to benefit our lives on Earth. NASA Spinoff highlights the Agency's most significant research and development activities and the successful transfer of NASA technology, showcasing the cutting-edge research being done by the Nation's top technologies and the practical benefits that come back down to Earth in the form of tangible products that make our lives better.

Source record↗

Cambium Documentation: Version 2021

Cambium is a tool that assembles structured data sets of simulated hourly emission, cost, and operational data for modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision-making. It was built to expand the metrics reported in the National Renewable Energy Laboratory's (NREL's) Standard Scenarios - an annually released set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, looking forward through 2050 (Cole et al. 2021) Information about Cambium and related publications can be found at https://nrel.gov/analysis/cambium.html, and the Cambium data sets for the Standard Scenarios can be viewed and downloaded at https://cambium.nrel.gov/. In this documentation, we define the metrics reported in Cambium databases (Section 4) and document the Cambium-specific methods for calculating those metrics (Section 5). As this document is intended to cover multiple Cambium data releases, we do not document specific scenarios here - for individual data releases, readers should look for an accompanying report that describes the assumptions and data that underlie that specific release. For Cambium databases that are built on NREL's Standard Scenarios, for example, reports describing the scenarios can be found on the Standard Scenarios web site (https://www.nrel.gov/analysis/standard-scenarios.html).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cambium 2024 Scenario Descriptions and Documentation

The National Renewable Energy Laboratory's (NREL's) Cambium data sets are annually released sets of simulated hourly data for a range of modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision- making. The 2024 Cambium data set is the fifth annual release. The data sets are a companion product to NREL's Standard Scenarios, which are likewise released annually and are a set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, but covering more scenarios with less temporal granularity. Information about Cambium and related publications can be found at https://www.nrel.gov/analysis/cambium.html, and the Cambium data sets can be viewed and downloaded at https://scenarioviewer.nrel.gov/. In this documentation, we describe Cambium 2024's scenarios, define the metrics, and document the Cambium-specific methods for calculating those metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

Cloud computing capabilities have rapidly expanded within the private sector, offering new opportunities for meteorological applications. Collaborations between NASA Marshall, NASA Ames, and contractor partners led to evaluations of private (NASA) and public (Amazon) resources for executing short-term NWP systems. Activities helped the Marshall team further understand cloud capabilities, and benchmark use of cloud resources for NWP and other applications

Disasters↗

Sensitivity of Next-Generation CMB Surveys to Neutrinos and Other Light Relics

Neutrinos and other light relics leave characteristic imprints in the cosmic microwave background anisotropies, making their observation a sensitive probe of the particle content and thermal history of the early universe. The energy density in these relativistic species is parameterized by their effective number $N_\mathrm{eff}$. Measuring this parameter at the percent level, which is a long-standing science goal of CMB-S4 and other experiments, would test a wide range of well-motivated physics within and beyond the Standard Model of particle physics. In this paper, we present Fisher-matrix forecasts of the projected sensitivity to $N_\mathrm{eff}$ of several CMB-S4 survey configurations considered during its extensive design phase. The conceptual design reaches $σ(N_\mathrm{eff}) < 0.03$ over its seven-year observing period, while the revised configuration achieves the same precision over a longer timescale. We complement these results with a cosmic-variance-limited survey over the same multipole range to quantify the room for improvement accessible with additional instrumental, observational, and theoretical efforts. Finally, we discuss the broad implications of precise $N_\mathrm{eff}$ measurements for the radiation sector, big bang nucleosynthesis, light thermal relics, and other early-universe physics. The forecasts presented in this work are performed with the publicly released DRAFT (Dark Radiation Anisotropy Flowdown Team) tool. It provides an end-to-end pipeline from simulated foreground maps and component separation to delensing and projected sensitivities for any cosmological parameter, and it can be directly applied to other cosmic microwave background survey designs.

Trendafilova, Cynthia [Case Western Reserve U., CE↗

The impacts of COVID-19 on clean energy labor markets: Evidence from multifaceted analysis of public health interventions and COVID-health factors

COVID-19 pandemic has affected clean energy labor market. Using real-time job vacancy data, this study analyzes the impacts of the pandemic on the U.S. clean energy labor market in 2020, including biomass, energy efficiency (EE), electric vehicle (EV), power/microgrid, solar, and wind industries. This study identifies how COVID-health factors and public health interventions influence clean energy job availability during the early COVID pandemic. Overall, California had the most energy jobs and experienced a significant decrease in April 2020. EV and solar had the highest percentages of job vacancies during the pandemic in general. Still, lockdowns had the most severe influence on EE and wind jobs. Stay-at-home orders negatively affected clean energy job vacancies in biomass, EV, power/microgrid, and wind. Social-gathering restrictions, however, did not have much influence. Increased COVID tests at the state level had the strongest and most positive influence on clean energy job postings, indicating the importance of a state's ability to manage public health infrastructure or crisis issues. COVID hospitalizations negatively influenced the job vacancies in biomass and wind but did not affect the other four sectors; conversely, as COVID death numbers increased, the number of jobs in biomass, EV, power grid, solar, and wind decreased, but not in EE jobs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗