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At least 289 records · Page 16

Characterizing Wet Season Precipitation in the Central Amazon Using a Mesoscale Convective System Tracking Algorithm

To comprehensively characterize convective precipitation in the central Amazon region, we utilize the Python FLEXible object TRacKeR (PyFLEXTRKR) to track mesoscale convective systems (MCSs) observed through satellite measurements and simulated by the Weather Research and Forecasting model at a convection-permitting resolution. This study spans a 2-month period during the wet seasons of 2014 and 2015. We observe a strong correlation between the MCS track density and accumulated precipitation in the Amazon basin. Key factors contributing to precipitation, such as MCS properties (number, size, rainfall intensity, and movement), are thoroughly examined. Our analysis reveals that while the overall model produces fewer MCSs with smaller mean sizes compared to observations, it tends to overpredict total precipitation due to excessive rainfall intensity for heavy rainfall events (≥10 mm hr –1 ). These biases in simulated MCS properties could vary with the constraints on the convective background environment. Moreover, while the wet bias from heavy (convective) rainfall outweighs the dry bias in light (stratiform) rainfall, the latter can be crucial, particularly when MCS cloud cover is significantly underestimated. A case study for 1 April 2014 highlights the influence of environmental conditions on the MCS lifecycle and identifies an unrealistic model representation in both stratiform and convective precipitation features.

54 ENVIRONMENTAL SCIENCES↗

Multi-Mission Power Analysis Tool (MMPAT) Version 3

The Multi-Mission Power Analysis Tool (MMPAT) simulates a spacecraft power subsystem including the power source (solar array and/or radioisotope thermoelectric generator), bus-voltage control, secondary battery (lithium-ion or nickel-hydrogen), thermostatic heaters, and power-consuming equipment. It handles multiple mission types including heliocentric orbiters, planetary orbiters, and surface operations. Being parametrically driven along with its user-programmable features can reduce or even eliminate any need for software modifications when configuring it for a particular spacecraft. It provides multiple levels of fidelity, thereby fulfilling the vast majority of a project s power simulation needs throughout the lifecycle. It can operate in a stand-alone mode with a graphical user interface, in batch mode, or as a library linked with other tools. This software can simulate all major aspects of a spacecraft power subsystem. It is parametrically driven to reduce or eliminate the need for a programmer. Added flexibility is provided through user-designed state models and table-driven parameters. MMPAT is designed to be used by a variety of users, such as power subsystem engineers for sizing power subsystem components; mission planners for adjusting mission scenarios using power profiles generated by the model; system engineers for performing system- level trade studies using the results of the model during the early design phases of a spacecraft; and operations personnel for high-fidelity modeling of the essential power aspect of the planning picture.

Wood, Eric G.↗

Asset Management: Beyond 2020

This Asset Management Beyond 2020 document provides: (1) an introduction to asset management (AM) and an asset management system (AMS), along with insights to next steps, (2) an overview of the International Standards Organization (ISO) 55000 series documents, (3) an overview of the ISO 55001 gap analysis of Center 4700/4800 ("Facilities") organizations at Sandia National Laboratories, hereafter referred to as Sandia, with observations, gaps, and gap closure recommendations, and (4) an asset management architecture (AMA) recommendation aligned with the ISO 55001. The AMS and the AM are different but related. ISO 55000 cites AMS as "a management system for AM" to "direct, coordinate, and control AM activities." ISO 55000 cites AM as translating "the organizational objectives into technical and financial decisions, plans and activities."1 Essentially, the AMS begins with all levels of leadership to enable a structured and consistent approach to AM culminating in lifecycle asset management excellence.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA's Software Safety Standard

NASA relies more and more on software to control, monitor, and verify its safety critical systems, facilities and operations. Since the 1960's there has hardly been a spacecraft launched that does not have a computer on board that will provide command and control services. There have been recent incidents where software has played a role in high-profile mission failures and hazardous incidents. For example, the Mars Orbiter, Mars Polar Lander, the DART (Demonstration of Autonomous Rendezvous Technology), and MER (Mars Exploration Rover) Spirit anomalies were all caused or contributed to by software. The Mission Control Centers for the Shuttle, ISS, and unmanned programs are highly dependant on software for data displays, analysis, and mission planning. Despite this growing dependence on software control and monitoring, there has been little to no consistent application of software safety practices and methodology to NASA's projects with safety critical software. Meanwhile, academia and private industry have been stepping forward with procedures and standards for safety critical systems and software, for example Dr. Nancy Leveson's book Safeware: System Safety and Computers. The NASA Software Safety Standard, originally published in 1997, was widely ignored due to its complexity and poor organization. It also focused on concepts rather than definite procedural requirements organized around a software project lifecycle. Led by NASA Headquarters Office of Safety and Mission Assurance, the NASA Software Safety Standard has recently undergone a significant update. This new standard provides the procedures and guidelines for evaluating a project for safety criticality and then lays out the minimum project lifecycle requirements to assure the software is created, operated, and maintained in the safest possible manner. This update of the standard clearly delineates the minimum set of software safety requirements for a project without detailing the implementation for those requirements. This allows the projects leeway to meet these requirements in many forms that best suit a particular project's needs and safety risk. In other words, it tells the project what to do, not how to do it. This update also incorporated advances in the state of the practice of software safety from academia and private industry. It addresses some of the more common issues now facing software developers in the NASA environment such as the use of Commercial-Off-the-Shelf Software (COTS), Modified OTS (MOTS), Government OTS (GOTS), and reused software. A team from across NASA developed the update and it has had both NASA-wide internal reviews by software engineering, quality, safety, and project management. It has also had expert external review. This presentation and paper will discuss the new NASA Software Safety Standard, its organization, and key features. It will start with a brief discussion of some NASA mission failures and incidents that had software as one of their root causes. It will then give a brief overview of the NASA Software Safety Process. This will include an overview of the key personnel responsibilities and functions that must be performed for safety-critical software.

Ramsay, Christopher M.↗

Connecting Research and Practice: An Experience Report on Research Infusion with SAVE

NASA systems need to be highly dependable to avoid catastrophic mission failures. This calls for rigorous engineering processes including meticulous validation and verification. However, NASA systems are often highly distributed and overwhelmingly complex, making the software portion of these systems challenging to understand, maintain, change, reuse, and test. NASA's systems are long-lived and the software maintenance process typically constitutes 60-80% of the total cost of the entire lifecycle. Thus, in addition to the technical challenges of ensuring high life-time quality of NASA's systems, the post-development phase also presents a significant financial burden. Some of NASA's software-related challenges could potentially be addressed by some of the many powerful technologies that are being developed in software research laboratories. Many of these research technologies seek to facilitate maintenance and evolution by for example architecting, designing and modeling for quality, flexibility, and reuse. Other technologies attempt to detect and remove defects and other quality issues by various forms of automated defect detection, architecture analysis, and various forms of sophisticated simulation and testing. However promising, most such research technologies nevertheless do not make the transition from the research lab to the software lab. One reason the transition from research to practice seldom occurs is that research infusion and technology transfer is difficult. For example, factors related to the technology are sometimes overshadowed by other types of factors such as reluctance to change and therefore prohibits the technology from sticking. Successful infusion might also take very long time. One famous study showed that the discrepancy between the conception of the idea and its practical use was 18 years plus or minus three. Nevertheless, infusing new technology is possible. We have found that it takes special circumstances for such research infusion to succeed: 1) there must be evidence that the technology works in the practitioner's particular domain, 2) there must be a potential for great improvements and enhanced competitive edge for the practitioner, 3) the practitioner has to have strong individual curiosity and continuous interest in trying out new technologies, 4) the practitioner has to have support on multiple levels (i.e. from the researchers, from management, from sponsors etc), and 5) to remain infused, the new technology has to be integrated into the practitioner's processes so that it becomes a natural part of the daily work. NASA IV&V's Research Infusion initiative sponsored by NASA's Office of Safety & Mission Assurance (OSMA) through the Software Assurance Research Program (SARP), strives to overcome some of the problems related to research infusion.

Lindvall, Mikael↗

The OSIRIS-REx Asteroid Sample Return Mission Operations Design

OSIRIS-REx is an acronym that captures the scientific objectives: Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer. OSIRIS-REx will thoroughly characterize near-Earth asteroid Bennu (Previously known as 1019551999 RQ36). The OSIRIS-REx Asteroid Sample Return Mission delivers its science using five instruments and radio science along with the Touch-And-Go Sample Acquisition Mechanism (TAGSAM). All of the instruments and data analysis techniques have direct heritage from flown planetary missions. The OSIRIS-REx mission employs a methodical, phased approach to ensure success in meeting the mission's science requirements. OSIRIS-REx launches in September 2016, with a backup launch period occurring one year later. Sampling occurs in 2019. The departure burn from Bennu occurs in March 2021. On September 24, 2023, the Sample Return Capsule (SRC) lands at the Utah Test and Training Range (UTTR). Stardust heritage procedures are followed to transport the SRC to Johnson Space Center, where the samples are removed and delivered to the OSIRIS-REx curation facility. After a six-month preliminary examination period the mission will produce a catalog of the returned sample, allowing the worldwide community to request samples for detailed analysis. Traveling and returning a sample from an Asteroid that has not been explored before requires unique operations consideration. The Design Reference Mission (DRM) ties together spacecraft, instrument and operations scenarios. Asteroid Touch and Go (TAG) has various options varying from ground only to fully automated (natural feature tracking). Spacecraft constraints such as thermo and high gain antenna pointing impact the timeline. The mission is sensitive to navigation errors, so a late command update has been implemented. The project implemented lessons learned from other "small body" missions. The key lesson learned was 'expect the unexpected' and implement planning tools early in the lifecycle. This paper summarizes the ground and spacecraft design as presented at OSIRIS-REx Critical Design Review(CDR) held April 2014.

mission operations↗

Application of Dynamical System Scaling for Accelerated Fuel Qualification Efforts

There are considerable ongoing research and testing campaigns to qualify new fuel designs such as metallic fuels for advanced reactor designs and the Accident Tolerant Fuel (ATF) campaign for light water reactors (LWR). The typical research and development lifecycle needed to qualify a nuclear fuel design, under ideal conditions, can take up to 20-25 years which limits the ability for new fuels to make fast deployments into commercial, test, and research reactors. While there are several efforts to accelerate nuclear fuel qualification through advanced modeling coupled with state-of-the-art experiments, there is not yet a framework to methodically quantify and rank distortions occurring in experimental test specimens needed to validate nuclear fuel performance codes. This study uses the Dynamical System Scaling (DSS) methodology to quantify transient scaling distortions that occur over experiment and simulated transients. DSS analysis metrics provide a researcher with several tools and information embedded within test data to identify dominant phenomena, associated timescales, and quantify a transient?s overall dynamic distortion. This is demonstrated with separate analyses of the SETH-C and CHF-SERTTA thermal-hydraulic experiments in the TREAT facility at Idaho National Laboratory. The outcome of this work is a scaling and data analysis approach to account for the influence a scaled fuel test specimen?s geometric and temporal distortions have on its ability to be representative of the full-scale design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Systems Engineering and Management Applications of ISO 9001:2015 for Government

The manufacturing segment of the business world is busy assessing the impact of ISO 9001:2015, and updating their management systems to meet the required compliance date. What does the new revision mean for government agencies that deliver large engineering projects rather than mass production? In fact, the standard, especially the new revision, can be used quite readily for government agencies, or applied to specific projects, once it is understood in terms of the similarities with systems engineering and project management. From there it can be extrapolated to "mission realization" systems, and a Quality Management System (QMS) is a logical result that can bring order to processes and systems that likely already exist in some fashion. ISO 9001:2015 is less product-oriented than previous versions. It can be more broadly applied to public organizations as well as private; and to services (missions) as well as products. The emphasis on risk management in the revised standard provides the needed balance for weighing decisions with respect to cost, schedule, technical, safety, and regulatory compliance; so if this is not part of agency governance already, this is a good place to start, especially for large engineering projects. The Systems Engineering standard used for this analysis is from NASA's NPR 7123.1 NASA Systems Engineering Processes and Requirements; however, those who are more familiar with ISO/IEC 26702 Systems Engineering-application and management of the systems engineering process, or SAE/EIA 632 Processes for Engineering a System will also recognize the similarities. In reality, the QMS outlined by ISO 9001 reinforces the systems engineering processes, and serves to ensure that they are adequately implemented, although most of the ISO 9001 literature emphasizes the production and process aspects of the standard. Rather than beginning with ISO 9001and getting lost in the vocabulary, it is useful to begin with the systems engineering lifecycle. Identification of stakeholder expectations, identifying solutions, creating specific product or service designs, production of the product or service, delivery to the public, and the associated management, planning, and control processes, are a familiar place to begin thinking of the overall system of identifying, designing, and competing a project or mission. Lining up this lifecycle with the ISO requirements (see Figure 1) illustrates how a quality management system is concerned with the same processes, and provides a governance and assurance function. If implemented properly, there are cost savings resulting from less rework, repair, reprocessing, failures, misplaced documents, and similar types of deficiencies1. Starting with an organization's systems engineering processes allows the organization to use their own terminology for a QMS plan, and tailor the plan to their own project or organization, so that it is more easily developed, understood, and implemented.

Shepherd, Christena C.↗

Quantitative approaches for including equity in risk and resilience infrastructure planning analyses

Risk and resilience assessments for critical infrastructure focus on myriad objectives, from natural hazard evaluations to optimizing investments. Although research has started to characterize externalities associated with current or possible future states, incorporation of equity priorities at project inception is increasingly being recognized as critical for planning related activities. However, there is no standard methodology that guides development of equity-informed quantitative approaches for infrastructure planning activities. Here, to address this gap, we introduce a logic model that can be tailored to capture nuances about specific geographies and community priorities, effectively incorporating them into different mathematical approaches for quantitative risk assessments. Specifically, the logic model uses a graded, iterative approach to clarify specific equity objectives as well as inform the development of equations being used to support analysis. We demonstrate the utility of this framework using case studies spanning aviation fuel, produced water, and microgrid electricity infrastructures. For each case study, the use of the logic model helps clarify the ways that local priorities and infrastructure needs are used to drive the types of data and quantitative methodologies used in the respective analyses. The explicit consideration of methodological limitations (e.g., data mismatches) and stakeholder engagements serves to increase the transparency of the associated findings as well as effectively integrate community nuances (e.g., ownership of assets) into infrastructure assessments. Such integration will become increasingly important to ensure that planning activities (which occur throughout the lifecycle of the infrastructure projects) lead to long-lasting solutions to meet both energy and sustainable development goals for communities.

community-based↗

Transition of Large-Scale Environmental Conditions and Characteristics of Four Rainfall Types Observed by S-PolKa During the MJO-1 Active Phase of DYNAMO/CINDY/AMIE

Analyses of National Center for Atmospheric Research (NCAR) S-PolKa dual-polarization radar data and ERA5 reanalysis fields indicate gradual changes in convection characteristics and large-scale environmental conditions during a central Indian Ocean Madden-Julian Oscillation (MJO) event observed by the DYNAMO/CINDY/AMIE field campaigns in late October 2011 (MJO-1). Examination of four rainfall types (isolated convective cores, convective, mixed, and stratiform) reveals a transition of convection characteristics (i.e., areal coverage and depth) between distinct 5-day environmental periods at the beginning and end of this ~2-week MJO active phase. A shift toward less frequent rainfall covering less of the radar domain for all four rainfall types occurs when large-scale lower-tropospheric dry air advects into the region with the westerly wind burst (WWB). Drier and warmer lower-free-tropospheric conditions associated with the WWB contribute to increased large-scale surface-based convective inhibition (CIN), surface-based convective available potential energy (CAPE), and cloud base heights. A thermodynamic budget analysis indicates reduced surface heat fluxes contribute to the increased surface-based CAPE. Greater CAPE at the end of MJO-1 coincides with deeper 50-dBZ convective echoes, while decreased 10-dBZ depth for all rainfall types corresponds in time with WWB-related dry-air advection. Increased (decreased) reflectivity values in the lower-level vertical reflectivity distribution of convective (stratiform) precipitation indicate increased (decreased) convective (stratiform) intensities when the WWB is present. The opposite depth changes for convective echoes and opposite shifts in convective and stratiform precipitation intensities underscore how the WWB can have differing impacts at different reflectivity thresholds and stages of the deep convection lifecycle.

54 ENVIRONMENTAL SCIENCES↗

Practical Application of PRA as an Integrated Design Tool for Space Systems

This paper presents the application of the first comprehensive Probabilistic Risk Assessment (PRA) during the design phase of a joint NASA/NOAA weather satellite program, Geostationary Operational Environmental Satellite Series R (GOES-R). GOES-R is the next generation weather satellite primarily to help understand the weather and help save human lives. PRA has been used at NASA for Human Space Flight for many years. PRA was initially adopted and implemented in the operational phase of manned space flight programs and more recently for the next generation human space systems. Since its first use at NASA, PRA has become recognized throughout the Agency as a method of assessing complex mission risks as part of an overall approach to assuring safety and mission success throughout project lifecycles. PRA is now included as a requirement during the design phase of both NASA next generation manned space vehicles as well as for high priority robotic missions. The influence of PRA on GOES-R design and operation concepts are discussed in detail. The GOES-R PRA is unique at NASA for its early implementation. It also represents a pioneering effort to integrate risks from both Spacecraft (SC) and Ground Segment (GS) to fully assess the probability of achieving mission objectives. PRA analysts were actively involved in system engineering and design engineering to ensure that a comprehensive set of technical risks were correctly identified and properly understood from a design and operations perspective. The analysis included an assessment of SC hardware and software, SC fault management system, GS hardware and software, common cause failures, human error, natural hazards, solar weather and infrastructure (such as network and telecommunications failures, fire). PRA findings directly resulted in design changes to reduce SC risk from micro-meteoroids. PRA results also led to design changes in several SC subsystems, e.g. propulsion, guidance, navigation and control (GNC), communications, mechanisms, and command and data handling (C&DH). The fault tree approach assisted in the development of the fault management system design. Human error analysis, which examined human response to failure, indicated areas where automation could reduce the overall probability of gaps in operation by half. In addition, the PRA brought to light many potential root causes of system disruptions, including earthquakes, inclement weather, solar storms, blackouts and other extreme conditions not considered in the typical reliability and availability analyses. Ultimately the PRA served to identify potential failures that, when mitigated, resulted in a more robust design, as well as to influence the program's concept of operations. The early and active integration of PRA with system and design engineering provided a well-managed approach for risk assessment that increased reliability and availability, optimized lifecyc1e costs, and unified the SC and GS developments.

Kalia, Prince↗

PV in the circular economy, a dynamic framework analyzing technology evolution and reliability impacts

Rapid, terawatt-scale deployment of photovoltaic (PV) modules is required to decarbonize the energy sector. Despite efficiency and manufacturing improvements, material demand will increase, eventually resulting in waste as deployed modules reach end of life. Circular choices for decommissioned modules could reduce waste and offset virgin materials. We present PV ICE, an open-source python framework using modern reliability data, which tracks module material flows throughout PV life cycles. We provide dynamic baselines capturing PV module and material evolution. PV ICE includes multimodal end of life, circular pathways, and manufacturing losses. We present a validation of the framework and a sensitivity analysis. Results show that manufacturing efficiencies strongly affect material demand, representing >20% of the 9 million tons of waste cumulatively expected by 2050. Reliability and circular pathways represent the best opportunities to reduce waste by 56% while maintaining installed capacity. Shorter-lived modules generate 81% more waste and reduce 2050 capacity by 6%.

14 SOLAR ENERGY↗

Green Biodegradation: Analysis of Potential Polyurethane-degrading Enzymes and Their Secretion in Chlamydomonas reinhardtii

Plastic pollution is a critical global issue, with only 5% of plastics currently recycled. Polyester polyurethane (PU), a widely used plastic, can potentially be broken down using enzymatic biodegradation rather than mechanical processing that generates microplastics. This study focuses on PS5, a potential PU-degrading enzyme with esterase activity, capable of cleaving ester bonds found in PU structures. Researchers investigated the expression and secretion of PS5 in the green microalga Chlamydomonas reinhardtii, a sustainable production platform capable of generating PU precursors such as lipids and diacids while sequestering carbon. Experiments demonstrated that PS5 significantly outperformed commercial lipase in cleaving the FDA substrate, indicating high esterase activity. Algal transformants expressing PS5 also showed halo formation on Impranil®-agar plates, suggesting PU dispersion degradation. These findings highlight C. reinhardtii as a viable chassis for the production and secretion of plastic-degrading enzymes, offering a sustainable route to both upcycle and degrade PU products at the end of their lifecycle.

Diaz, Crisandra Jade↗

Assessment of Model Hub Height Wind Speed Performance Using DOE Lidar Buoy Data

As the offshore wind industry continues to gain momentum both in the U.S. and globally, reanalysis products remain essential tools for the lifecycle of a wind farm. From project siting and production estimates to determining construction and maintenance windows, reanalysis products play an important role. These regional and global long-term models also serve as inputs to higher resolution models. With such wide-ranging impacts on the offshore wind industry, the need for validation of reanalysis products is strong, particularly at typical turbine hub heights. Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinelTM buoys for the U.S. Department of Energy (DOE) in order to collect meteorological and oceanographic data, including hub height wind speed, in areas of interest for offshore wind development. This work uses DOE buoy observations off the coasts of New Jersey and Virginia to evaluate the performance of Modern Era Retrospective Analysis for Research and Applications-2 (MERRA-2), the North American Regional Reanalysis (NARR), the European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th generation (ERA5), and the National Oceanic and Atmospheric Administration (NOAA) assimilation system Rapid Refresh (RAP). Biases and degrees of correspondence are determined for each reanalysis product in order to provide insights on the performance and uncertainty for long-term wind resource characterization. With the baseline metrics determined, this work proceeds with an investigation into the sources of large deviations between the modeled and observed hub height wind speeds during the East Coast lidar buoy deployments. Consistent sources of reanalysis model error include stably stratified flow conditions, high wind shear, flow parallel to the coastline, and tropical and winter storms. For the near shore New Jersey location, offshore winds (i.e. blowing from land to water) tend to be associated with model overestimation of observed hub height wind speed, while winds parallel to the coastline are correlated with model underestimation of wind speed. Similarly, near the Virginia buoy, during southerly winds (parallel to the coastline) models underestimate the observed wind speed due to coastal upwelling. Reanalysis model wind speeds underestimate the hub height winds with increasing stable atmospheric stratification. Reanalysis model biases are seen when the observed wind speeds approach or exceed typical turbine cut-out speeds (around 20 m s-1). Large model errors during winter and tropical storm events, high wind speed events, and ramp events are often the result of wind speed timing and magnitude offsets. Overall, ERA5 provides the most successful representation of observed offshore hub height wind speeds at the U.S. East Coast buoy locations and is therefore best suited as an input boundary condition for model case studies. ERA5 performs well for a variety of atmospheric phenomena, including storms and sea breezes, however RAP, the next most successful reanalysis model, performs best in capturing the frequency of ramp events.

17 WIND ENERGY↗

A Business Case Evaluation of Gas Switching Reforming (GSR) Technology: A Promising Technology for Natural Gas Reforming with Integrated CO2 Capture

Hydrogen is essential in the transition to sustainable energy, and developing low-carbon production methods is a key research focus. Traditional steam methane reforming (SMR) dominates the hydrogen industry but contributes substantially to CO2 emissions. In response, Gas Switching Reforming (GSR) has emerged as a novel process that integrates carbon capture and utilizes process heat more efficiently. Unlike other reforming methods, GSR consolidates oxidation and reduction reactions within a single reactor, which minimizes external energy inputs and simplifies scaling. Like conventional steam methane reforming (SMR), GSR can be integrated with water-gas shift and pressure swing adsorption units for pure hydrogen production. This work presents a comprehensive business case analysis of GSR technology based on experimental results in Technology Readiness Level 3, Life Cycle Assessment (LCA) and Techno-Economic (TEA) evaluation incorporating ASPEN Plus process modeling considering different configurations and energy scenarios. The TEA incorporates data from kinetic experiments from various catalysts to evaluate the GSR process under various conditions. The goal of this work is to evaluate GSR’s potential to serve as a low-carbon alternative to SMR, focusing on global warming potential and additional impact categories to evaluate a wide spectrum of environmental impacts. Comparative assessments were conducted with SMR, chemical loop reforming (CLR), and proton exchange membrane (PEM) electrolysis to explore trade-offs across environmental metrics. The environmental impact assessment of this work encompasses the entire hydrogen production lifecycle from raw material extraction to plant decommissioning, using a cradle-to-gate boundary. Preliminary findings highlight that GSR, when integrated with low-carbon energy sources, could significantly reduce environmental impacts, making it a promising candidate for low-carbon hydrogen infrastructure. The insights from this business case evaluation aim to guide industry in scale-up and commercialization of this promising clean energy technology.

03 NATURAL GAS↗

Choosing a software design method for real-time Ada applications: JSD process inversion as a means to tailor a design specification to the performance requirements and target machine

The validity of real-time software is determined by its ability to execute on a computer within the time constraints of the physical system it is modeling. In many applications the time constraints are so critical that the details of process scheduling are elevated to the requirements analysis phase of the software development cycle. It is not uncommon to find specifications for a real-time cyclic executive program included to assumed in such requirements. It was found that prelininary designs structured around this implementation abscure the data flow of the real world system that is modeled and that it is consequently difficult and costly to maintain, update and reuse the resulting software. A cyclic executive is a software component that schedules and implicitly synchronizes the real-time software through periodic and repetitive subroutine calls. Therefore a design method is sought that allows the deferral of process scheduling to the later stages of design. The appropriate scheduling paradigm must be chosen given the performance constraints, the largest environment and the software's lifecycle. The concept of process inversion is explored with respect to the cyclic executive.

Withey, James V.↗

Event Report for The Ethical Artificial Intelligence Quantification Workshop

Artificial Intelligence (AI) is a powerful emerging technology area which requires special attention to using it ethically. AI ethics is still an emerging field, and the partners for this workshop and report seek to move AI ethics discussion ahead by experimenting with ways to measure AI ethics criteria. The following document describes the outcomes and learnings from The Ethical Artificial Intelligence Quantification Workshop held at the National Institute for Aerospace (NIA), Hampton, Virginia on May 12th, 2022. The purpose of the workshop was for participants to evaluate and experiment-with the methodology and process presented by AIEthics.World in cooperation with Intel Corporation. The meeting participants learned about the Ethical AI Certification and Maturity Model™ and applied the methodology to selected notional AI systems. The workshop facilitated the evaluation of the maturity of the AI system according to ethical considerations relevant to NASA, NIA and other participants. The workshop consisted of three main phases. The first phase focused on understanding and summarizing NASA’s ethical approaches, mission and values based on published documentation, discussions and individual insights & opinions of participants. This information was prioritized, weighted, ordered, and quantified in phase two, to formulate an alignment between human values (ethics) and their applicability to AI systems during all lifecycle phases. The first two phases were summarized as a form of ethical genealogy for artificial intelligence, specific to NASA’s ethical approaches. In the third and last phase of the workshop the participants evaluated notional examples of artificial intelligence to qualify and quantify its ability to adhere to the organizational ethics approaches, using the Ethical AI Certification and Maturity Model™. The workshop uses the concept of genealogy, in the traditional sense: the study and traceability of lines of ancestors in the process of evolutionary development from earlier forms. However, as it is applied to an Ethical AI definition, it is providing the insights to the necessary and mandatory traceability of content, data, metrics, telemetry, elements, and structures which are used in the AI’s lifecycle to foster and measure AI ethics in all steps of its lifecycle. The Ethical Artificial Intelligence Quantification Workshop provided NASA with the opportunity to apply the Ethical AI Certification and Maturity Model™, in combination with existing and well-known decision-making and quality control methods to identify the metrics and measurements for an Ethical AI and assess its ethical condition and quality aligned with NASA ethics approaches. The result of the workshop is the capacity for NASA to apply the maturity model assessment to its AI Systems as desired and if necessary, publish the ability of these AI Systems to adhere to the organizational ethical goals. AI ethics frameworks need to be customized for each application domain, for example, individual NASA Mission Directorates. General principles that work in one area such as AI/Machine Learning-based text analysis (the ethics of information-extraction) may need to be adapted for another such as sense-and-avoid decision-making in a flight environment. The workshop was conducted among approximately twenty NASA subject matter experts, so the elements noted above should be considered examples, not definitive NASA ethical AI principles, genealogy, etc. Generating a definitive AI ethics framework for an organization as diverse as NASA would require far more discussion, debate, review, etc. However, the workshop provided valuable insight into mechanisms and processes for quantifying AI ethical qualities.

Artificial Intelligence↗

Optimizing Hydronic Heating for Comfort and Performance in Multifamily Housing

Inefficient control settings in multifamily boilers often lead to substantial energy and cost penalties. To address this, a Fault Detection and Diagnostic (FDD) tool was developed to automate data analysis and identify operational faults such as suboptimal outdoor temperature sensor placement, misconfigured outdoor air reset (OAR) curves, excess boiler cycling, and domestic hot water (DHW) setpoint errors. By comparing pre- and post-implementation periods and applying engineering models, the tool quantifies energy savings and reduces manual analysis time by over 90%. Testing on over 100 monitored sites and a targeted subset of 12 buildings showed an average 11% energy savings from remote optimization; further validation across 19 OAR curve changes confirmed the tool’s accuracy, predicting actual savings within ±5% for most cases. Simple payback can be under three years for many multifamily buildings, though rising hardware, labor, and fuel costs create uncertainties, and decarbonization goals increasingly shift focus to electrification. The FDD tool remains invaluable for optimizing existing boilers, enhancing future electrification measures, and adapting to new technologies by refining building load estimates. In doing so, it supports both near-term efficiency and long-term transitions to low-carbon alternatives, ensuring buildings achieve substantial cost and energy benefits throughout their system lifecycles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗