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Exploring Mission Concepts with the JPL Innovation Foundry A-Team

The JPL Innovation Foundry has established a new approach for exploring, developing, and evaluating early concepts called the A-Team. The A-Team combines innovative collaborative methods with subject matter expertise and analysis tools to help mature mission concepts. Science, implementation, and programmatic elements are all considered during an A-Team study. Methods are grouped by Concept Maturity Level (CML), from 1 through 3, including idea generation and capture (CML 1), initial feasibility assessment (CML 2), and trade space exploration (CML 3). Methods used for each CML are presented, and the key team roles are described from two points of view: innovative methods and technical expertise. A-Team roles for providing innovative methods include the facilitator, study lead, and assistant study lead. A-Team roles for providing technical expertise include the architect, lead systems engineer, and integration engineer. In addition to these key roles, each A-Team study is uniquely staffed to match the study topic and scope including subject matter experts, scientists, technologists, flight and instrument systems engineers, and program managers as needed. Advanced analysis and collaborative engineering tools (e.g. cost, science traceability, mission design, knowledge capture, study and analysis support infrastructure) are also under development for use in A-Team studies and will be discussed briefly. The A-Team facilities provide a constructive environment for innovative ideas from all aspects of mission formulation to eliminate isolated studies and come together early in the development cycle when they can provide the biggest impact. This paper provides an overview of the A-Team, its study processes, roles, methods, tools and facilities.

Team Eureka↗

ESIP Earth Sciences Data Analytics (ESDA) Cluster - Work in Progress

The purpose of this poster is to promote a common understanding of the usefulness of, and activities that pertain to, Data Analytics and more broadly, the Data Scientist; Facilitate collaborations to better understand the cross usage of heterogeneous datasets and to provide accommodating data analytics expertise, now and as the needs evolve into the future; Identify gaps that, once filled, will further collaborative activities. Objectives Provide a forum for Academic discussions that provides ESIP members a better understanding of the various aspects of Earth Science Data Analytics Bring in guest speakers to describe external efforts, and further teach us about the broader use of Data Analytics. Perform activities that:- Compile use cases generated from specific community needs to cross analyze heterogeneous data- Compile sources of analytics tools, in particular, to satisfy the needs of the above data users- Examine gaps between needs and sources- Examine gaps between needs and community expertise- Document specific data analytics expertise needed to perform Earth science data analytics Seek graduate data analytics Data Science student internship opportunities.

science data analysis↗

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

data analytics↗

Hybrid Electric Propulsion Technologies for Commercial Transports

NASA Aeronautics Research Mission Directorate has set strategic research thrusts to address the major drivers of aviation such as growth in demand for high-speed mobility, addressing global climate and capitalizing in the convergence of technological advances. Transitioning aviation to low carbon propulsion is one of the key strategic research thrust and drives the search for alternative and greener propulsion system for advanced aircraft configurations. This work requires multidisciplinary skills coming from multiple entities. The Hybrid Gas-Electric Subproject in the Advanced Air Transportation Project is energizing the transport class landscape by accepting the technical challenge of identifying and validating a transport class aircraft with net benefit from hybrid propulsion. This highly integrated aircraft of the future will only happen if airframe expertise from NASA Langley, modeling and simulation expertise from NASA Ames, propulsion expertise from NASA Glenn, and the flight research capabilities from NASA Armstrong are brought together to leverage the rich capabilities of U.S. Industry and Academia.

electric motor vehicles↗

NASA Weather Support 2017

In the mid to late 1980's, as NASA was studying ways to improve weather forecasting capabilities to reduce excessive weather launch delays and to reduce excessive weather Launch Commit Criteria (LCC) waivers, the Challenger Accident occurred and the AC-67 Mishap occurred.[1] NASA and USAF weather personnel had advance knowledge of extremely high levels of weather hazards that ultimately caused or contributed to both of these accidents. In both cases, key knowledge of the risks posed by violations of weather LCC was not in the possession of final decision makers on the launch teams. In addition to convening the mishap boards for these two lost missions, NASA convened expert meteorological boards focusing on weather support. These meteorological boards recommended the development of a dedicated organization with the highest levels of weather expertise and influence to support all of American spaceflight. NASA immediately established the Weather Support Office (WSO) in the Office of Space Flight (OSF), and in coordination with the United Stated Air Force (USAF), initiated an overhaul of the organization and an improvement in technology used for weather support as recommended. Soon after, the USAF established a senior civilian Launch Weather Officer (LWO) position to provide meteorological support and continuity of weather expertise and knowledge over time. The Applied Meteorology Unit (AMU) was established by NASA, USAF, and the National Weather Service to support initiatives to place new tools and methods into an operational status. At the end of the Shuttle Program, after several weather office reorganizations, the WSO function had been assigned to a weather branch at Kennedy Space Center (KSC). This branch was dismantled in steps due to further reorganization, loss of key personnel, and loss of budget line authority. NASA is facing the loss of sufficient expertise and leadership required to provide current levels of weather support. The recommendation proposed herein is to re-establish the WSO under a high level office, with funding set at about the same levels as today, with a revitalized charter and focus to allow for the WSO to operate as originally intended.

lessons learned↗

From Apollo to the Future, the NASA Curation Model for Engaging the Sample Science Community Maximizes Science on Extraterrestrial Samples

The Astromaterials Acquisition and Curation Office at Johnson Space Center (JSC) has enjoyed a long-term partnership (50 years!) with a broad community of planetary sample scientists. This partnership has enabled the curators of planetary samples to plan for and enact evolving requirements for preservation of sample scientific integrity and for handling and long-term storage. The basis for this relationship is a standing peer review advisory committee composed of leading scientists who are recognized for achievements in sample analysis. The committee and its descendants have brought familiarity with the most relevant scientific investigations and the associated analytical and contamination challenges. Beginning with Apollo, the review committee was charged with oversight of curatorial operations and with ensuring fair access to samples. As additional samples from other planetary bodies were acquired, the committee evolved, taking on new responsibilities, reflected in committee name changes. However, oversight of curatorial operations and fair allocation of samples remain basic responsibilities. Committee recommendations are sent to the NASA Headquarters Discipline Scientist for approval. To minimize conflict of interest and maximize fair access, the rules governing the make-up of the committee is structured. Systematic rotation of leadership and staggered terms of membership allow the committee to retain expertise while bringing in fresh ideas. The first peer review committee was called the Lunar Sample Analysis and Planning Team (LSAPT) and was formalized in early 1968 with about 15 members. Their function was to review a) the equipment and procedures used in the new Lunar Receiving Laboratory (LRL); b) the proficiency and capability of the LRL staff; c) the sequence of sample analysis and allocation after quarantine release; and d) the findings of the Preliminary Examination Team (PET). According to LSAPT member Gerald Wasserburg, one of the first issues they faced was deciding whether to have most of the sample analyses performed in house at the LRL or to distribute samples to members of the scientific community. LSAPT concluded that the major scientific investigations should be carried out externally to the LRL by scientists chosen for their expertise in specific disciplines. Further they recommended that the PET's basic characterization of samples be circulated to the broad scientific community. LSAPT set its own agenda, paid attention to facility details, closely monitored the move of samples from the LRL to the interim curatorial facility in 1973, and was active in inspecting curation facilities. Between 1975 and 1979, a Facility Subcommittee of LSAPT oversaw the design and construction of a permanent facility for preservation of lunar samples. The result was an outstanding facility still in use today. In 1977, a separate peer review committee, the Meteorite Working Group (MWG), was formed to evaluate requests for new meteorites then being collected in Antarctica under what would in 1980 become a 3-agency agreement (National Science Foundation, NASA, Smithsonian Institution). By 1979, after lunar samples were moved into the new permanent facility, the vacated gloveboxes and laboratory were prepared for meteorite curation. Recognizing that LSAPT had been helpful in setting up the JSC curatorial facility for Antarctic meteorites, JSC recommended the review committee be given expanded duties, including advice on curation and analysis of materials from other planetary bodies and the name be changed to Lunar and Planetary Sample Team (LAPST). In 1993, LAPST was renamed the Curation and Analysis Planning Team for Extraterrestrial Materials (CAPTEM) to reflect additional functions. CAPTEM is chartered to be (1) a community-based, interdisciplinary forum for discussion and analysis of matters concerning the collection and curation of extraterrestrial samples, including planning future sample return missions and (2) a standing review panel, charged with evaluating proposals requesting allocation of all extraterrestrial samples contained in NASA collections. Efficiency and flexibility are gained through use of subcommittees, both ad hoc and standing. Transition of the MWG to a subcommittee of CAPTEM was completed in 2017. Today subcommittees review allocation requests for lunar samples, Antarctic meteorites, cosmic dust, Stardust cometary samples, Genesis solar wind samples, and samples returned from asteroids. Other subcommittees address facilities, informatics, and micro-cratered substrates. Planetary samples have been sent to research teams in over 30 countries world-wide. The expertise in the care and fair distribution of astromaterials by NASA using this model spans generations of planetary sample scientists and is a valuable resource to be tapped for future sample returns - OSIRIS-REx, Hayabusa 2, and Mars 2020.

Allton, Judith↗

Recent Activities of the Marshall Space Flight Center Natural Environments Branch Terrestrial & Planetary Environments Team

- The Natural Environments (NE) Branch is within the MSFC Engineering Directorate’s Spacecraft and Vehicle System (S&VS) Department - S&VS plans, performs and directs the technical Design, Analysis, Test, Evaluation, Verification, Integration, and Applied Research and Development of future Spacecraft and Launch Vehicle Systems - Current programs we support - Space Launch System, Human Landing System, Mars Ascent Vehicle, Orion, Gateway - NE maintains expertise in terrestrial, space, and planetary natural environments definition, characterization, and analysis - Responsibility to disseminate this expertise to Agency programs and projects in support of environment definition, requirements development, vehicle development, operations, and sustaining engineering through program’s life cycle - Branch has two teams; Terrestrial and Planetary Environments (T&PE) and Space Environments (SE) - T&PE has extensive expertise characterizing terrestrial surface and atmospheric (aloft) environments - Winds, temperature, humidity, pressure, lightning, density, precipitation, radiant energy, aerosols, sea state, sea surface temperature - Maintains climatological databases for engineering analyses

Ryan K. Decker↗

NASA Support for Commercial Crew Launch Capabilities

Since the earliest days of U.S. human spaceflight, NASA’s Marshall Space Flight Center in Huntsville, Alabama, has played a key role in American crew launch capability, from engineering support for the first Mercury-Redstone launches, to the Saturn launches to the Moon, through Shuttle and now Artemis. Today, Marshall brings that expertise gained through decades of crewed space launches to NASA’s Commercial Crew Program (CCP), providing launch vehicle engineering and programmatic support. The team’s responsibilities have included human certification of commercial launch systems for the CCP missions, including Atlas V and Falcon 9, and verifying each launch vehicle complies with flight certification. MSFC provides expertise in nearly all aspects of launch vehicle design and performance including solid motors and liquid engines, stage propulsion, thrust vector control, structural and dynamics, safety and mission assurance. During each commercial crew launch, an engineering support team is on console at Marshall’s Huntsville Operations Support Center, which has provided launch operations support since Apollo, providing real-time oversight to safety standards for the vehicle and verifying data. Launch vehicle support for Commercial Crew has come as a paradigm shift for the MSFC team, inspiring new approaches that leverage expertise and best practices from past NASA-developed launch vehicle missions, while at the same time providing new synergies from work with commercial partners on CCP. This paper will explore the role that the Marshall launch vehicle services team plays in the Commercial Crew Program, as well as lessons learned from the program that will continue to benefit a new era of spaceflight partnerships.

Commercial Crew↗

Content and Representation of Information Needed to Support Time-Constrained Problem Solving

NASA’s current mission-operations paradigm originated with Project Mercury and endured with minimum evolution through the Apollo Program, Space Shuttle Program, and ISS missions. At its foundation is a near-complete real-time dependence on a ground team to manage the combined state of the mission, vehicle, and crew. Utilizing many engineers and operators with broad and deep expertise; large, distributed datasets including extensive telemetry; and expansive analytical and computing power, this ground team has served as the safety net for crewed spaceflight missions over the past 60 years. This approach must change to address challenges associated with missions beyond low Earth orbit (BLEO), including infrequent resupply, reduced ability to evacuate, and delayed communications that prohibit real-time operational support. We anticipate that a necessary part of this change will be increased independence for the crew, as roles and responsibilities traditionally performed by ground teams move on board the vehicle. While many risks are associated with Earth-independent operations, one particular concern is ensuring that the crew will have adequate onboard support to perform urgent problem solving when communication with the ground is delayed or intermittent. A key resource that enables the ground team to respond to anomalies quickly and effectively is the extraordinary expertise and experience it possesses. It is comprised of 80+ experts on at any given time, with a combined 600+ years of system-specific experience across 22 unique console disciplines. A small crew will face the unprecedented challenge of independently responding to anomalies that have historically been handled by a team 20 times their size. Another important resource upon which the ground heavily relies to support procedure execution and anomaly response is data. The amount of telemetry data that each flight controller monitors is extensive. In addition, as the ground team works to further assess impacts, trouble shoot, identify workarounds, and oversee procedure execution, it accesses and synthesizes engineering and procedure information, as well as system build, test, and configuration documentation. It is not feasible nor useful to put all these data onboard as crews become more Earth independent. Each member of a small Mars mission small crew will have multiple roles beyond monitoring telemetry and data gathering, and multiple roles within anomaly resolution processes, thereby limiting their capacity for copious amounts of information. Moreover, while access is necessary, it alone is insufficient. Information will need to be compiled, refined, and represented appropriately to support the crew’s reduced attention and expertise. This work seeks to understand the content and representation of information needed to support time-constrained problem solving and decision making by the crew without real-time ground support. To build this understanding, we first surveyed the literature, focusing on how expert problem solvers construct and manipulate their mental models. Next, we interviewed expert problem solvers in spaceflight and analogous domains and surveyed industry solutions for data presentation. Finally, we analyzed current spaceflight operations by investigating flight controller anomaly resolution processes during ISS training simulations and real operational events. These methods led to creating a problem-solving framework that details common themes and features of attending to, assessing, analyzing, and acting on problems in complex, time-constrained domains. Using this framework and the results of our analysis, we identified conceptual data representations needed for crew-led problem-solving. Preliminary onboard user interface concepts to meet identified needs will be presented.

anomaly response↗

Briefing Human Reliability Analysis Tasks in the KINS-INL Project

Under the SPP with Korea Institute of Nuclear Safety (KINS) (SPP No. 24SP91), INL research team has a plan to visit KINS on December 3, 2024 and have a project meeting with KINS in-person. INL researchers will give this presentation about what we have done on Task 2 under the contract as below. Task 2: Support KINS in the treatment of human actions. INL efforts consist of: Provide technical expertise on recovery analysis based on INL’s methods or recent research Provide technical expertise on dependency analysis based on INL’s methods or recent research Provide technical expertise on analyzing the effects of HSI degradation on operator actions

99 - GENERAL AND MISCELLANEOUS↗

Radiochemistry and nuclear chemistry workforce in the United States

The disciplines of radiochemistry and nuclear chemistry have direct applications in the fields of national security, nuclear medicine, nuclear power production, and environmental management. Although, often, nuclear and radiochemistry are grouped together and many experts work in both areas, the definition for each field is slightly different. For example, radiochemistry may be defined as the application of the phenomena of radioactive decay and techniques common to nuclear physics so as to solve problems in the field of chemistry. In contrast, nuclear chemistry may be defined as the application of procedures and techniques common to chemistry to study the structure of the atomic nucleus. This chapter provides a brief update of the current state of, and critical U.S. needs for, nuclear chemistry and radiochemistry expertise as the Assuring a Future U.S.-Based Nuclear and Radiochemistry Expertise report was published by National Academy of Sciences (NAS) in 2012.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Overcoming Barriers to Radiopharmaceutical Therapy (RPT): An Overview From the NRG-NCI Working Group on Dosimetry of Radiopharmaceutical Therapy

Radiopharmaceutical therapy (RPT) continues to demonstrate tremendous potential in improving the therapeutic gains in radiation therapy by specifically delivering radiation to tumors that can be well assessed in terms of dosimetry and imaging. Dosimetry in external beam radiation therapy is standard practice. This is not the case, however, in RPT. This NRG (acronym formed from the first letter of the 3 original groups: National Surgical Adjuvant Breast and Bowel Project, the Radiation Therapy Oncology Group, and the Gynecologic Oncology Group)-National Cancer Institute Working Group review describes some of the challenges to improving RPT. The main priorities for advancing the field include (1) developing and adopting best practice guidelines for incorporating patient-specific dosimetry for RPT that can be used at both large clinics with substantial resources and more modest clinics that have limited resources, (2) establishing and improving strategies for introducing new radiopharmaceuticals for clinical investigation, (3) developing approaches to address the radiophobia that is associated with the administration of radioactivity for cancer therapy, and (4) solving the financial and logistical issues of expertise and training in the developing field of RPT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Under-capacitated and over-powered? Rural austerity and asymmetrical negotiating relationships in US wind energy development

Though rural local governments are central actors in renewable energy development, local governments in the United States (US) remain systematically under-funded. This paper considers what the manifestations of austerity in local governments broadly and rural localities specifically mean for renewable energy development and for energy transitions. Drawing on a survey of 262 elected county officials with experience with wind energy in eight US states, this paper asks how local officials understand the impacts of wind development, how local governments are involved in wind energy negotiations, how the resources and expertise needed to navigate negotiations are distributed among counties, and analyze the relationship between local capacity, access to resources, and involvement in negotiations. We find that local officials express simultaneously affective and material concerns with the impacts of wind development and see negotiations with the developer as central to realizing local benefits. However, the expertise and staffing needed to negotiate with developers is less accessible to poorer or sparsely populated counties, and counties with lower overall revenues have narrower scopes of negotiation, and counties incre. Our results suggest that uneven rural capacity heightens an already asymmetrical relationship between localities and developers. In analyzing how infrastructure developments are shaped by relationships between localities and developers that are conditioned by austerity and (under)capacity, this paper contributes to and bridges scholarly discussions on rural austerity, rescaling, and renewable energy transitions. These results challenge conventional wisdoms around centralizing energy siting processes, contextualize popular and academic debates about opposition to renewable energy development, and highlight the need for rural reinvestment to realize meaningfully participatory energy developments.

Elmallah, Salma↗

Corrigendum to ‘Under-capacitated and over-powered? Rural austerity and asymmetrical negotiating relationships in US wind energy development’ [J. Rural Stud., 119 (2025) 1–14]

The authors regret that there is an incomplete sentence in the abstract of the article, and request that the portion “, and counties incre” be deleted from the abstract (found at the end of the sentence beginning with “However …”). The portion to be deleted is underlined and bolded below. The authors would like to apologise for any inconvenience caused. Current abstract: Though rural local governments are central actors in renewable energy development, local governments in the United States (US) remain systematically under-funded. This paper considers what the manifestations of austerity in local governments broadly and rural localities specifically mean for renewable energy development and for energy transitions. Drawing on a survey of 262 elected county officials with experience with wind energy in eight US states, this paper asks how local officials understand the impacts of wind development, how local governments are involved in wind energy negotiations, how the resources and expertise needed to navigate negotiations are distributed among counties, and analyze the relationship between local capacity, access to resources, and involvement in negotiations. We find that local officials express simultaneously affective and material concerns with the impacts of wind development and see negotiations with the developer as central to realizing local benefits. However, the expertise and staffing needed to negotiate with developers is less accessible to poorer or sparsely populated counties, and counties with lower overall revenues have narrower scopes of negotiation, and counties incre. Our results suggest that uneven rural capacity heightens an already asymmetrical relationship between localities and developers. In analyzing how infrastructure developments are shaped by relationships between localities and developers that are conditioned by austerity and (under)capacity, this paper contributes to and bridges scholarly discussions on rural austerity, rescaling, and renewable energy transitions. These results challenge conventional wisdoms around centralizing energy siting processes, contextualize popular and academic debates about opposition to renewable energy development, and highlight the need for rural reinvestment to realize meaningfully participatory energy developments.

Elmallah, Salma↗

Developing a common approach for classifying building stock energy models

Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, here we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling

Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.

AI↗

The role of peer review and science for advancing public understanding

We live in a time of rapid change. The Covid-19 pandemic has united the world to understand and develop solutions to protect the health and wellbeing of society. At the same time, access to information on the internet and social media has exploded. People are exposed to information with many claims. Some of the information is relevant and accurate. A significant fraction may be inaccurate, biased, and potentially dangerous. With Covid-19, the information might point to cures that are toxic or risks that are not relevant. The scientific community has developed a process to develop and convey knowledge. The validation of results and their interpretation is critical to advancing knowledge. The core of the scientific process is based on developing a hypothesis-driven concept, designing and executing an experimental approach to prove or disprove the hypothesis, conducting a statistical analysis of the results to confirm their validity, and interpreting their meaning and impact. When their work is completed the scientist prepares to publish the work. Publication requires peer review. Hypotheses, experimental approaches, results, and interpretation of results are independently and anonymously reviewed by a scientific peer. The reviewers are selected based on their expertise in the field. The peer review process is essential for the integrity of the scientific process. Without a robust scientific process, society cannot discriminate between validated results and interpretations and biased, inaccurate, and potentially dangerous conjecture. With inaccurate science society and policy makers may make poor decisions that could hurt people and the world around them. While scientists should not censor information available to the public, scientists have a responsibility to inform the public. We must articulate what the scientific process is and why it is essential when considering the validity of information. Scientist are responsible for pointing out when public information has not been vetted through a scientific process and therefore cannot be considered conclusive. Scientists are responsible for highlighting information that has been generated and vetted with the scientific process. Over time, our goal is for the public to value the scientific process based on peer review. The public could become enlightened to the necessity for peer review to support decisions and action. Scientists need to contribute to advancing public knowledge. When invited to serve as a peer reviewer, scientists have a responsibility to contribute to the process. We all are extremely busy making peer review a distraction. While peer review does not directly benefit our own work and career, it benefits our chosen field of science. This is very important for the research area that our journal, Water-Energy Nexus, is focusing on. We cover the convergence of science and technology integrating across large spatial ranges (micro to global) in environmental pollution and the balance of remediation issues with energy use. Water-Energy Nexus wants to provide scientists with a platform for scientific debate and discussion on this rich and complicated topic. With the manuscripts submitted to WEN cover integrated research topics across a broad range of subjects from environment sciences through energy engineering, the role of peer review is essential. Peer review on a new submission to WEN should not be biased towards a specific science field. It should be done considering the complex nature of issues in the water-energy nexus. Scientists need to contribute to the public dialog. To accomplish these goals, we need to be honest, accurate, articulate, and use understandable language. The impact of WEN is very diverse affecting society in many ways. The scientific audience for WEN is diverse and readers may not fully understand the content of the papers outside their research expertise. Therefore, scientists, especially those who want to contribute to WEN, should work with communications specialists to convey message to benefit society. The audience includes the general public and researchers outside the author’s core specialty. While the peer-reviewed journal article is the cornerstone of our careers and critical for advancing scientific knowledge, a general interest story could benefit society even more. The author cannot lose sight that our work has two audiences, the science community, and more importantly, our family, friends, neighbors, and policy makers.

54 ENVIRONMENTAL SCIENCES↗

The Value of Forecasters‐in‐the‐Loop in Real‐Time Flood Forecasting in the Age of Machine Learning

Machine learning (ML) applications in hydrological forecasting are increasingly prevalent and show great potential. However, many previous studies have only evaluated performance through reanalysis or retrospective simulations compared to simplified baselines. This study provides the first assessment of ML performance against actual operational forecasting systems operated by the California Nevada River Forecast Center (CNRFC), which combines the Community Hydrologic Prediction System (CHPS) with forecasters-in-the-loop. Results demonstrate that forecasters-in-the-loop systems consistently outperform ML models in both general forecasts and flood alerting across lead times up to 96 hr, even when ML models use observed forcings, while CNRFC operational process relies on biased weather forecasts. Our analysis reveals that forecaster expertise maintains forecast reliability despite inaccurate precipitation inputs, with human-guided systems showing superior performance degradation characteristics at extended lead times. These findings highlight the irreplaceable value of human expertise in operational forecasting and caution against overstating current ML capabilities in real-world applications.

Tran, Vinh Ngoc [Univ. of Michigan, Ann Arbor, MI ↗