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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Stakeholder-Engaged Structured Decision Making for the Los Alamos Legacy Cleanup Mission - 20501

The Los Alamos National Laboratory (LANL) environmental legacy cleanup program requires decisions to be made for environmental remediation, decommissioning and disposal or management of radioactive waste. This legacy cleanup program was established to address groundwater contamination, material disposal areas (MDAs) that have been used to dispose of radioactive and other waste material, and 'aggregate areas' that might produce radioactive or other chemical waste as a result of remediation activities. The LANL site is regulated for environmental concerns under the Resource Conservation and Recovery Act (RCRA). However, some parts of LANL, such as material disposal area G (MDA G), have disposed of radioactive waste under DOE Order 435.1, and are subject to other regulations. For example, decommissioning the remote-handled TRU material stored in 33 shafts at MDA G falls under EPA's 40 CFR 191. Collectively, the regulations are all aimed in the same direction of finding the best solution, either through constructs such as 'as low as reasonably achievable' (ALARA), considering balancing factors as opposed to only cost and human health risk, and, under EPA regulations such as RCRA and NEPA, evaluating impact from all chemicals and both human health and ecological endpoints. Despite the basic goals and objectives of the regulations or their guidance, the main challenge is in their implementation. Arguably perhaps, but really in principle, all of these (and similar) regulations are asking for a decision analysis to be performed. Implementation challenges encountered have included lack of understanding of decision analysis in the industry, lack of effective stakeholder engagement in the decision analysis process, and lack of appreciation of the need to separate value judgments from science, the latter leading to developing conservative, or protective, science-based models. Conservative models lead to poor solutions, lack of effective stakeholder engagement leads to long drawn out protracted approaches to finding a solution (which also might never be found with this approach), and lack of understanding of decision analysis and Bayesian statistics causes poor models to be built, which creates unfortunate situations of 'garbage in, garbage out' becoming the basis for decision making. Stakeholder-engaged structured decision making (SDM) is an approach to solving problems that relies on the theory of decision science to involve stakeholders in the decision-making process. This approach incorporates stakeholder values using a scientifically rigorous methodology that separates value judgments from science in a way that helps avoid the pitfalls of biased, protective, or conservative modeling. This approach has its foundation in Keeney's 1992 treatise on value-focused thinking [1]. Keeney advocated a paradigm shift in decision making based on the idea that the standard way of thinking about decisions is backwards. The standard approach of focusing first on identifying alternatives rather than on articulating values results in a reactive approach with the emphasis on mechanics and fixed choices instead of the core values that have meaning to stakeholders. This paradigm shift effectively engages all stakeholders in the decision-making process while using a values focused thinking approach that can lead to the identification of decision opportunities and the creation of better alternatives. The intent is to be proactive and generate solutions that are related directly to values and objectives as identified by stakeholders. There are, perhaps, two overarching reasons why SDM can be used to benefit LANL's environmental legacy cleanup. Some of LANL's remaining waste management and environmental management problems are challenging and complex (for example, the Cr and RDX plumes, and MDAs) and while the traditional approach has, arguably, worked well for relatively simple risk-based problems, it cannot, or should not, be applied to more complex problems if the most effective and efficient solutions are desired. The second reason is cost. This has perhaps become more critical since publication of the Government Accountability Office (GAO) reports that DoE's environmental liability is considered a high-risk concern for the nation [2]. The focus of SDM is on structuring solutions to decision risk problems by first addressing stakeholder and decision maker values and subsequently developing decision objectives and ways to measure those objectives, preference weighting across objectives, identifying decision alternatives that best achieve those values, and characterizing uncertainty in predictions of the measures. Because a complete decision model is created using SDM, it can be evaluated to find the main elements of the model that drive, or predict, the best solution. This approach creates complete decision models that are transparent, traceable, reproducible and technically defensible. The science behind SDM, or decision analysis, is well founded, yet it is not unusual to see ad hoc approaches to decision making implemented under various environmental regulations that are pertinent to the LANL site, including NEPA, RCRA and DOE Order 435.1. Such ad hoc approaches are often not transparent or traceable, and lack reproducibility and technical defensibility. The LANL legacy cleanup program has embarked on using SDM to address the complex problems that remain. Stakeholder meetings have been held, and a prototype version of the stakeholder value system has been developed. Further meetings are expected in the future to address specific project needs. This is a long-term endeavor considering the complex environmental problems faced by DOE EM in Los Alamos (EM-LA), and careful planning, consideration of stakeholder value systems, and engagement with stakeholders throughout the SDM process is expected to lead to a successful endpoint. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Real-time Simulation of Coordinated Sub-Transmission Volt-Var Control Tool under High Distributed PV Penetration

With the rapid penetration of intermittent solar photovoltaic (PV) and other distributed energy resources (DER) into the grid, and subsequent changes in power flow patterns in both distribution and sub-transmission, voltage regulation is becoming a major challenge. It is prudent to leverage PV and DER to provide ancillary services to the grid, such as voltage regulation. Recently, a quasi-static, coordinated real-time sub transmission volt-var control algorithm (CReST-VCT) was developed for voltage regulation under high PV penetration by dispatching the reactive power settings of the shunt devices and PV inverters. The algorithm was validated offline, on a quasistatic study. Such quasi-static dispatching algorithms cannot guarantee its performance for highly nonlinear dynamical power systems. In this paper the performance of the algorithm is validated with a real time nonlinear dynamic simulation of a modified IEEE 118 bus system in Opal-RT. The real time simulation is used to emulate the actual system operation, providing a more realistic testing environment for CReST-VCT. The dispatch and control signals are communicated between the power system (Opal solver) and the control center (GAMS solver) in real-time with a MODBUS bridge. The results demonstrate i) system is stable with the new dispatch points ii) significant improvement in system-wide voltage profiles compared to an uncontrolled scenario. Another significant contribution of the work is developing a framework for dispatchable, long duration dynamic simulations that can be leveraged for market/dispatch studies.

CReST-VCT, Opal-RT, Volt/Var Control, renewable in↗

The evolution of transcriptional regulation in eukaryotes

Gene expression is central to the genotype-phenotype relationship in all organisms, and it is an important component of the genetic basis for evolutionary change in diverse aspects of phenotype. However, the evolution of transcriptional regulation remains understudied and poorly understood. Here we review the evolutionary dynamics of promoter, or cis-regulatory, sequences and the evolutionary mechanisms that shape them. Existing evidence indicates that populations harbor extensive genetic variation in promoter sequences, that a substantial fraction of this variation has consequences for both biochemical and organismal phenotype, and that some of this functional variation is sorted by selection. As with protein-coding sequences, rates and patterns of promoter sequence evolution differ considerably among loci and among clades for reasons that are not well understood. Studying the evolution of transcriptional regulation poses empirical and conceptual challenges beyond those typically encountered in analyses of coding sequence evolution: promoter organization is much less regular than that of coding sequences, and sequences required for the transcription of each locus reside at multiple other loci in the genome. Because of the strong context-dependence of transcriptional regulation, sequence inspection alone provides limited information about promoter function. Understanding the functional consequences of sequence differences among promoters generally requires biochemical and in vivo functional assays. Despite these challenges, important insights have already been gained into the evolution of transcriptional regulation, and the pace of discovery is accelerating.

Review, Academic↗

Shape‐Stabilization of Phase Change Materials with Carbon‐Conscious Poly(hydroxy)Urethane Foams

Thermal energy regulation is a significant challenge, contributing to over 30% of annual greenhouse gas emission (GHG) emissions. Phase change materials (PCMs) offer a promising solution by storing thermal energy, which can enable the reuse of waste heat for heating and cooling; however, developing materials for shape-stabilized PCMs remains crucial. This work investigates a self-foaming poly(hydroxy)urethane (PHU), derived from a non-isocyanate polyurethane (NIPU), as a porous support for shape-stabilizing paraffinic and salt hydrate PCMs. PHU-encapsulated paraffinic PCMs exhibited excellent thermal stability over repeated cycles. Thermal stability with salt hydrate PCMs, specifically calcium chloride hexahydrate (CaCl 2 •6H 2 O), is achieved by the incorporation of 5 wt.% barium carbonate (BaCO 3 ) into the PHU foam. This enabled stable cycling for over 48 cycles with desirable thermal properties, i.e., a melting point ≈30 °C, high enthalpy (ca. 138 J g −1 per cycle), and a consistent freezing point ≈20 °C, making it suitable for applications in buildings and electric vehicle battery insulation. Also, incorporating graphite (1.5–10 wt.%) into the foam enhanced the thermal conductivity of shape-stabilized CaCl 2 •6H 2 O during heating and cooling cycles. Overall, the approach detailed here offers a carbon-conscious and chemically tunable material for thermal energy storage.

25 ENERGY STORAGE↗

Emerging Tools to Support DILI Assessment in Clinical Trials with Abnormal Baseline Serum Liver Tests or Pre-existing Liver Diseases

Abstract Based on the late Dr. Hyman Zimmerman’s observation that hepatocellular drug-induced liver injury (DILI) leading to jaundice carries a ≥ 10% fatality risk (coined as Hy’s law by others), evaluation of Drug-Induced Serious Hepatotoxicity (eDISH) continues to play a central role in the assessment of a study drug’s liability for acute hepatocellular DILI. The eDISH identifies drugs in clinical trials with DILI fatality (death or transplant) risk that may be unacceptable in a post-market setting. As a two-dimensional graph that plots peak total bilirubin (TB) versus peak serum aminotransferase levels for each patient during study drug or comparator treatment, eDISH identifies potential cases of acute, modest, and serious hepatocellular DILI for in-depth analysis of liver tests (LT) and clinical course so that the likelihood of causal association with the study drug can be determined. Unfortunately, the generalizable utility of this tool only pertains to trials enrolling patients with normal or near normal (NNN) baseline (BL) serum LTs. The eDISH does not necessarily apply to trials of patients with abnormal baseline (ABN-BL) LTs that often coincide with underlying liver disorders. Because drug development programs being reviewed by the FDA increasingly target liver disorders, we are often challenged to evaluate DILI risk in trials of patients with ABN-BL LTs. Also, the high background prevalence of metabolic dysfunction associated steatotic liver disease (MASLD) means patients with LTs above NNN may need to be enrolled in trials treating non-liver disorders to reflect the target population. Such study populations create challenges for industry and regulators because eDISH may not reliably categorize or identify potential cases of DILI for further analysis, as it so efficiently does in NNN-BL trials. We describe the main functionalities of eDISH in NNN-BL trials to understand what should be emulated by new tools or eDISH modifications. We then discuss non-eDISH–based plots that may be useful in ABN-BL trials.

Amirzadegan, Jasmine↗

The key role of the ferroptosis mechanism in neurological diseases and prospects for targeted therapy

Neurological disorders represent a major global health concern owing to their intricate pathological processes. Ferroptosis, defined as a form of cell death that is reliant on iron, has been closely linked to various neurological conditions. The fundamental process underlying ferroptosis is defined by the excessive buildup of iron ions, which initiates lipid peroxidation processes leading to cellular demise. Neurons, as highly metabolically active cells, are susceptible to oxidative stress, and imbalances in iron metabolism can directly initiate the ferroptosis process. In neurodegenerative disorders like Alzheimer’s disease and Parkinson’s disease, ferroptosis driven by iron accumulation represents a fundamental pathological connection. Although the connection between ferroptosis and neurological diseases is clear, clinical application still faces challenges, such as precise regulation of iron metabolism, development of specific drugs, and assessment of efficacy. The limited comprehension of the ferroptosis mechanism hinders the development of personalized treatment approaches. Consequently, subsequent investigations must tackle these obstacles to facilitate the clinical application of ferroptosis-associated therapies in neurological disorders. This article provides a comprehensive overview of the most recent advancements regarding the underlying mechanisms of ferroptosis. Subsequently, the study investigates the mechanistic contributions of ferroptosis within the nervous system. In conclusion, we evaluate and deliberate on targeted therapeutic strategies associated with ferroptosis and neurological disorders.

Xie, Chenyu↗

Sustainable Biofuels for Low-Carbon Maritime Transportation

The marine shipping sector heavily depends on fossil fuels and is one of the largest petroleum fuel consumers [1,2]. The annual global marine fuel consumption was estimated to be around 400 million metric tons in 2019 (2.5 billion barrels). Moreover, ocean shipping is one of the most significant contributors to sulfur oxides, nitrogen oxides, and particulate matter emissions. Global shipping contributes 13% of human-caused sulfur emissions and 2.6% of anthropogenic carbon dioxide emissions. As a major source of pollutant emissions, the marine industry faces several challenges related to emission regulations. The International Maritime Organization (IMO) has established a framework for reducing the carbon intensity of shipping: 40% reduction relative to 2008 levels by 2030 and 70% reduction by 2050. As the aviation sector, the maritime shipping sector is difficult to decarbonize through electrification. Biofuels offer the best opportunities for decarbonizing marine shipping in the near and medium-term. Advanced biofuels such as pyrolysis bio-oil offer the low-cost potential for meeting carbon reduction goals. For instance, the pyrolysis bio-oil exhibited promising marginal CO2 abatement costs at less than $100/tonne CO2-equivalent at a heavy fuel oil price greater than $1.10/gal [1]. As a potential biofuel option for low-carbon maritime shipping, this presentation focuses on a comparative techno-economic analysis (TEA) of bio-oils produced via a fast pyrolysis-based conversion pathway. The pathway converts a 50/50 blend of forest residues and clean pine to bio-oil via three process options: fast pyrolysis without vapor upgrading, and fast pyrolysis with vapor phase upgrading over ZSM-5 zeolite catalyst and Pt/TiO2 catalyst. The process configuration and operation variation led to different capital and operating costs, as well as the resulting raw bio-oil’s yield and quality, e.g., the water content, total acid number, and carboxylic acid number. The study also determined the minimum upgrading of bio-oils required to enable blending with very low sulfur fuel oil (VLSFO), with the associated costs reflected in TEA. This study shows that bio-oil could be a cost-effective fuel option for decarbonizing maritime shipping. Further research is required with respect to biofuel blending properties, such as compatibility with existing fuel system infrastructure and suitable engine performance.

BIOMASS FUELS↗

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗

Deep Reinforcement Scheduling of Energy Storage Systems for Real-time Voltage Regulation in Unbalanced LV Networks with High PV Penetration

The ever-growing higher penetration of distributed energy resources (DERs) in low-voltage (LV) distribution systems brings both opportunities and challenges to voltage support and regulation. This paper proposes a deep reinforcement learning (DRL)-based scheduling scheme of energy storage systems (ESSs) to mitigate system voltage deviations in unbalanced LV distribution networks. The ESS-based voltage regulation problem is formulated as a multi-stage quadratic stochastic program, with the objective of minimizing the expected total daily voltage regulation cost while satisfying operational constraints. While existing voltage regulation methods are mostly focused on onetime- step control, this paper explores a day-horizon systemwide voltage regulation problem. In other words, the size of action and state spaces are extremely high-dimensional and need to be delicately handled. Furthermore, in order to overcome the difficulty of modeling uncertainties and develop a realtime solution, a learn-to-schedule feedback control framework is proposed by adapting the problem to a model-free DRL setting. The proposed algorithm is tested on a customized 6-bus system and a modified IEEE 34-bus system. Simulation results validate the effectiveness and near-optimality of voltage regulation by ESS in comparison with a deterministic quadratic program solution.

Wang, Shengyi↗

Control-oriented core-SOL-divertor model to address integrated burn and divertor control challenges in ITER

The real-time regulation of a burning plasma’s temperature and density, or burn control, will be necessary to produce high fusion power in future tokamaks like ITER. This is made more challenging due to the plasma’s nonlinear characteristics and the interdependence between the core-plasma and edge-plasma regions. For example, a raising plasma temperature leads to increasing reactivity and therefore to more alpha-particle heating, which further increases temperature. Furthermore, a raise of the fusion power increases the heat flow through the scrape-off-layer (SOL), which can compromise the integrity of the divertor without proper safeguards. For control design, a model-based approach is attractive because it can directly incorporate the nonlinear, coupled, burning-plasma dynamics into the design. To facilitate this design approach, a control-oriented core-SOL-divertor (CSD) model is presented in this work. In this CSD model, a core-plasma model captures the nonlinear dynamics of the core’s density and temperature, and a SOL-divertor model defines the plasma conditions at the separatrix and divertor including the heat load on the target plates. The core-plasma and SOL-divertor models are coupled through the exchange of various variables. In particular, the SOL-divertor model yields the separatrix temperature and the influx of recycled particles into the core-plasma. Further, these variables influence the power and particle balances captured by the core-plasma model. In return, the core-plasma model determines the intensity of the heat and particles fluxes across the separatrix, and this outflow strongly impacts the SOL-divertor model. Therefore, the power and density of the core-plasma, which can be readily modulated through external heating systems and pellet injection, can be viewed as control knobs for the SOL-divertor region in addition to the gas puffing. In simulations of the CSD model, it is demonstrated how external actuation can be utilized to meet burn control and divertor control objectives simultaneously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimal Distribution System Voltage Regulation using State Estimation and DER Grid-Support Functions

Increasing solar energy penetrations may create challenges for distribution system operations because production variability can lead to large voltage deviations or protection system miscoordination. Instituting advanced management systems on distribution systems is one promising method for combating these challenges by intelligently controlling distribution assets to regulate voltage and ensure protection safety margins. While it is generally not the case today, greater deployment of power system sensors and interoperable distributed energy resources (DER)e.g., photovoltaic (PV) inverters, energy storage systems (ESS), electric vehicles (EVs)will enable situational awareness, control, and optimization of distribution systems. In this work, a control system was created which measures power system parameters to estimate the status of a feeder, forecasts the distribution state over a short-term horizon, and issues optimal set point commands to distribution-connected equipment to regulate voltage and protect the system. This two-year project integrated multiple research innovations into a management system designed to safely allow PV penetrations of 50% or greater. The integrated software was demonstrated through extensive real-time (RT) and power hardware-in-the-loop studies and a field demonstration on a live power system with a 684 kVA PV system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Making coal relevant for small scale applications: Modular gasification for syngas/engine CHP applications in challenging environments

Small-scale coal gasification technology, coupled to a reciprocating engine generator, has the potential for making coal a cost competitive resource for meeting the flexible energy needs and resiliency requirements of utilities across the United States. To maintain grid stability and reliability, electrical generation must be regulated to match the load at the proper voltage and frequency. With the expansion of intermittent sources into the grid, such as wind and solar, frequency and voltage regulation become increasingly important and challenging. This work presents the results of a Front End Engineering Design (FEED) effort to detail the engineering and preliminary economics of a small-scale, air blown, fixed-bed gasification process, operating at near-atmospheric pressure, with gas cleanup to provide syngas and pyrolysis liquid fuels for use in reciprocating engine generators for combined heat and power at the University of Alaska Fairbanks. A very detailed assessment of capital and operating costs allows the evaluation of a levelized cost of electricity of 208.06 $/MWh, which can be reduced through the selling of by-products (steam for heating purposes and pyrolysis liquids to be used for power generation in an existing diesel engine). Here, a combined sensitivity analysis, based on the Monte Carlo approach, has been carried out to evaluate the effects of the uncertainties (capital and operating costs and plant annual availability) on the LCOE.

01 COAL, LIGNITE, AND PEAT↗

State Regulatory Opportunities to Advance Distributed Energy Resource Aggregations in Wholesale Markets

The report discusses how state regulators can promote the participation of DERs in wholesale markets, including complementary actions that they can take to support Federal Energy Regulatory Commission Order 2222 implementation. It also summarizes wholesale market operators’ Order 2222 compliance and associated compliance challenges along with potential state regulator roles. The report identifies actions that state regulators can take to accelerate DER aggregations providing grid services.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

All Hazards Approach to Grid Modernization

Resilience hazards for electric power systems are on the rise, exacerbated by both a rise in extreme weather events and manmade physical and cyber attacks. At the same time, grid modernization challenges plague the United States, covering everything from increased electrification and ambitious renewable energy targets to aging infrastructure and regulation that lags behind today’s challenges. This talk will cover an all-hazards risk based approach that addresses both rising resilience and grid modernization challenges. Examples of this approach taken for national laboratory research projects will be discussed, including a deep dive into a project that addressed black start, resynchronization, distributed control, and cybersecurity challenges for an operational microgrid up to sub-transmission voltages. As takeaways from this project are translated from demonstration scale to real-world exercises, key lessons are noted on the translation from research into practice and how this can inform risk-based research moving forward

17 WIND ENERGY↗

Cyber-Physical Dynamic System (CPDS) Modeling for Frequency Regulation and AGC Services of Distributed Energy Resources

The substantial integration of renewable energy brings significant challenges to balance the system in real time because of the variability and intermittency of renewable power. For the reliable system operation, the frequency regulation service is used to stabilize the system frequency through automatically balancing the system generation and load. On one hand, with the substantially increasing deployment of renewable energy in electricity system, the requirement of frequency regulation (FR) services increases significantly. On the other hand, the current main resource of FR services, the controllable conventional generation, is continuously decreasing in the system generation mix. This means that in the future high renewable penetration power system, additional and alternative reliable FR services providers such as distributed energy storage (DES) resources should be explored. Although the capability of utility-scale energy storage to provide FR services has been demonstrated, the integrated control and dynamic modeling of distributed energy resource (DER) providing frequency regulation grid services has been rarely explored. There are several challenges to adopt DERs to provide reliable grid services as illustrated in FERC 755. First, the distributed installation of DES requires a comprehensive cyber-physical dynamic system (CPDS) modeling to fully consider the impacts of the communication latency variability on its real time FR provision capability. Unlike the conventional generators, there are two-layer communication between DERs and system operators which increase the communication delay. Second, unlike the conventional generators whose dynamic models have been comprehensively studied, the difference among individual DER components' power-dynamic characteristic brings challenges in the accurate dynamic AGC modeling of its power-frequency relationship. Third, the temporal dependent state of charge uncertainty of DERs challenges DERs' power and frequency regulation capacities scheduling in the look-ahead generation scheduling. Therefore, the aggregator should optimize the frequency regulation provision from individual DER in real time. To overcome these challenges, this project proposes a cyber-physical dynamic system (CPDS) model to handle the uncertainty of DERs two-layer communication latency and power dynamics. The variability of DERs' communication delay and dynamic constraints will be comprehensively modeled. The DERs' AGC model with communication delay is designed to validate DESs' frequency regulation services. Like current performance-based frequency regulation evaluation, the delivery of DERs' frequency regulation will be assessed through post-analysis of the actual AGC response with respect to the AGC control signal from system operators. Consequently, the reliability improvement with DERs providing reliable frequency regulation services can be evaluated from a comprehensive perspective considering all the dynamics of communication and power.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A structural description of the evolution of stakeholders and risk communication in the Department of Energy's defense nuclear facilities: Historical perspective, major stakeholders, and external events

Regulators and policymakers are routinely challenged with explaining complex concepts concerning risk. Part of the challenge is helping external and internal stakeholders to understand the context behind risk-related information and decisions. Here, this paper will describe the historical evolution of the safety and regulatory framework for an important category in the nuclear industry—defense nuclear facilities owned and operated by the US Department of Energy. In parallel with describing this evolution, three major events which occurred external to the complex of defense nuclear facilities will be summarized, and their impact on the maturation of the Department's safety and regulatory framework will be discussed. Finally, integrated with these two threads of discussion will be a chronicle of the changing set of involved organizations and the expanding set of external stakeholders involved in risk decisions—and therefore, the risk communications ecosystem surrounding defense nuclear facilities. It will be noted that this system was once describable as a classic “iron triangle,” but now has progressed to a complex network of federal and state organizations, numerous congressional committees, and expanding sets of external stakeholders. It is hoped that a comprehensive discussion of the context of risk assessment in the defense nuclear facilities complex—addressing historical insights, organizational evolution, and the maturing structure of regulation—will provide enhanced opportunities for building trust and understanding in this complex environment.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Proteome reallocation enables the selective de novo biosynthesis of non-linear, branched-chain acetate esters

The one-carbon recursive ketoacid elongation pathway is responsible for making various branched-chain amino acids, aldehydes, alcohols, and acetate esters in living cells. Controlling selective microbial biosynthesis of these target molecules at high efficiency is challenging due to enzyme promiscuity, regulation, and metabolic burden. In this study, we present a systematic modular design approach to control proteome reallocation for selective microbial biosynthesis of branched-chain acetate esters. Through pathway modularization, we partitioned the branched-chain ester pathways into four submodules including keto-isovalerate submodule for converting pyruvate to keto-isovalerate, ketoacid elongation submodule for producing longer carbon-chain keto-acids, ketoacid decarboxylase submodule for converting ketoacids to alcohols, and alcohol acyltransferase submodule for producing branched-chain acetate esters by condensing alcohols and acetyl-CoA. By systematic manipulation of pathway gene replication and transcription, enzyme specificity of the first committed steps of these submodules, and downstream competing pathways, we demonstrated selective microbial production of isoamyl acetate over isobutyl acetate. In this work, we found that the optimized isoamyl acetate pathway globally redistributed the amino acid fractions in the proteomes and required up to 23-31% proteome reallocation at the expense of other cellular resources, such as those required to generate precursor metabolites and energy for growth and amino acid biosynthesis. From glucose fed-batch fermentation, the engineered strains produced isoamyl acetate up to a titer of 8.8 g/L (> 0.25 g/L toxicity limit), a yield of 0.22 g/g (61% of maximal theoretical value), and 86% selectivity, achieving the highest titers, yields and selectivity of isoamyl acetate reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

Abstract Vegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

54 ENVIRONMENTAL SCIENCES↗