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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 703 records · Page 39

A decentralized software bus based on IP multicas ting

We describe decentralized reconfigurable implementation of a conference management system based on the low-level Internet Protocol (IP) multicasting protocol. IP multicasting allows low-cost, world-wide, two-way transmission of data between large numbers of conferencing participants through the Multicasting Backbone (MBone). Each conference is structured as a software bus -- a messaging system that provides a run-time interconnection model that acts as a separate agent (i.e., the bus) for routing, queuing, and delivering messages between distributed programs. Unlike the client-server interconnection model, the software bus model provides a level of indirection that enhances the flexibility and reconfigurability of a distributed system. Current software bus implementations like POLYLITH, however, rely on a centralized bus process and point-to-point protocols (i.e., TCP/IP) to route, queue, and deliver messages. We implement a software bus called the MULTIBUS that relies on a separate process only for routing and uses a reliable IP multicasting protocol for delivery of messages. The use of multicasting means that interconnections are independent of IP machine addresses. This approach allows reconfiguration of bus participants during system execution without notifying other participants of new IP addresses. The use of IP multicasting also permits an economy of scale in the number of participants. We describe the MULITIBUS protocol elements and show how our implementation performs better than centralized bus implementations.

Callahan, John R.↗

Route Generation for a Synthetic Character (BOT) Using a Partial or Incomplete Knowledge Route Generation Algorithm in UT2004 Virtual Environment

This paper presents a new Route Generation Algorithm that accurately and realistically represents human route planning and navigation for Military Operations in Urban Terrain (MOUT). The accuracy of this algorithm in representing human behavior is measured using the Unreal Tournament(Trademark) 2004 (UT2004) Game Engine to provide the simulation environment in which the differences between the routes taken by the human player and those of a Synthetic Agent (BOT) executing the A-star algorithm and the new Route Generation Algorithm can be compared. The new Route Generation Algorithm computes the BOT route based on partial or incomplete knowledge received from the UT2004 game engine during game play. To allow BOT navigation to occur continuously throughout the game play with incomplete knowledge of the terrain, a spatial network model of the UT2004 MOUT terrain is captured and stored in an Oracle 11 9 Spatial Data Object (SOO). The SOO allows a partial data query to be executed to generate continuous route updates based on the terrain knowledge, and stored dynamic BOT, Player and environmental parameters returned by the query. The partial data query permits the dynamic adjustment of the planned routes by the Route Generation Algorithm based on the current state of the environment during a simulation. The dynamic nature of this algorithm more accurately allows the BOT to mimic the routes taken by the human executing under the same conditions thereby improving the realism of the BOT in a MOUT simulation environment.

Hanold, Gregg T.↗

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗

Discovery of first-in-class inhibitors of ASH1L histone methyltransferase with anti-leukemic activity

ASH1L histone methyltransferase plays a crucial role in the pathogenesis of different diseases, including acute leukemia. While ASH1L represents an attractive drug target, developing ASH1L inhibitors is challenging, as the catalytic SET domain adapts an inactive conformation with autoinhibitory loop blocking the access to the active site. Here, by applying fragment-based screening followed by medicinal chemistry and a structure-based design, we developed first-in-class small molecule inhibitors of the ASH1L SET domain. The crystal structures of ASH1L-inhibitor complexes reveal compound binding to the autoinhibitory loop region in the SET domain. When tested in MLL leukemia models, our lead compound, AS-99, blocks cell proliferation, induces apoptosis and differentiation, downregulates MLL fusion target genes, and reduces the leukemia burden in vivo. This work validates the ASH1L SET domain as a druggable target and provides a chemical probe to further study the biological functions of ASH1L as well as to develop therapeutic agents.

60 APPLIED LIFE SCIENCES↗

COX-2/sEH Dual Inhibitor PTUPB Potentiates the Antitumor Efficacy of Cisplatin

Cisplatin-based therapy is highly toxic, but moderately effective in most cancers. Concurrent inhibition of cyclooxygenase-2 (COX-2) and soluble epoxide hydrolase (sEH) results in antitumor activity and has organ-protective effects. The goal of this paper was to determine the antitumor activity of PTUPB, an orally bioavailable COX-2/sEH dual inhibitor, in combination with cisplatin and gemcitabine (GC) therapy. NSG mice bearing bladder cancer patient-derived xenografts were treated with vehicle, PTUPB, cisplatin, GC, or combinations thereof. Mouse experiments were performed with two different PDX models. PTUPB potentiated cisplatin and GC therapy, resulting in significantly reduced tumor growth and prolonged survival. PTUPB plus cisplatin was no more toxic than cisplatin single-agent treatment as assessed by body weight, histochemical staining of major organs, blood counts, and chemistry. The combination of PTUPB and cisplatin increased apoptosis and decreased phosphorylation in the MAPK/ERK and PI3K/AKT/mTOR pathways compared with controls. PTUPB treatment did not alter platinum–DNA adduct levels, which is the most critical step in platinum-induced cell death. The in vitro study using the combination index method showed modest synergy between PTUPB and platinum agents only in 5637 cell line among several cell lines examined. However, PTUPB is very active in vivo by inhibiting angiogenesis. Finally, PTUPB potentiated the antitumor activity of cisplatin-based treatment without increasing toxicity in vivo and has potential for further development as a combination chemotherapy partner.

60 APPLIED LIFE SCIENCES↗

System-of-systems optimization of hydrogen infrastructure for heavy-duty freight corridors: The interstate 10 case study

Medium and heavy-duty freight transportation requires hydrogen energy infrastructure that is cost-effective, operationally reliable, spatially coherent, and resilient to demand variability along major corridors. This paper presents an integrated hydrogen corridor planning framework using Oak Ridge National Laboratory's OR-AGENT that couples freight-driven, route-resolved hydrogen demand modeling with optimized station siting, sizing, and station-level techno-economic analysis. The framework is demonstrated for the Interstate 10 freight corridor and the Houston-to-Los-Angeles region. Hydrogen demand is derived from high-resolution origin–destination freight data, duty-cycle characterization, and physics-based energy consumption modeling. Candidate refueling sites are selected from existing heavy-duty diesel fueling locations and optimized subject to onboard storage and station capacity constraints. Resulting station throughputs are evaluated using established techno-economic models for electrolytic hydrogen production and dispensing infrastructure. Results show that a regional, portfolio-level aggregation, average dispensed electrolytic hydrogen cost of $6.87–$7.26/kg is currently feasible, and is strongly influenced by demand density and utilization.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗

Feedback Power Cost Optimization in Power Distribution Networks with Prosumers

Here, we propose a feedback control approach for solving optimal power flow (OPF) problems in power distribution networks (DNs) based on a projected gradient scheme, where the cost is given by the sum of functions of local power injections. This approach does not require detailed knowledge of the grid model and enables real-time tracking of the optimal generation configuration. Moreover, the communication burden is minimal: only a broadcast from a central entity, called the Network Supervisor (NS), to the agents in the network is needed. Hence, agents do not have to share local information that can be sensitive, e.g., their power injections or the value of the local costs. Our approach is then used to solve a particular OPF problem targeting DNs with high penetration of distributed energy resources (DERs) in which the energy cost is given by the remuneration that the DERs owners receive for the service they provide.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CodeScribe Agent

SF-26-086 CodeScribe introduces a structured, multi-stage pipeline that combines deterministic program analysis with LLM-powered translation to enable incremental, testable Fortran-to-C++ migration. First, `code-scribe index` traverses the project directory tree and produces `scribe.yaml` metadata files recording all modules, subroutines, and functions at each level, giving the LLM accurate structural context instead of a hallucinated codebase model. Second, `code-scribe draft` performs the deterministic portion of translation — converting Fortran types to C++ equivalents, replacing `use` statements with `#include` and `using namespace` directives, and detecting constructs requiring special handling — while embedding`scribe-prompt` annotations that guide the LLM through non-trivial cases such as statement-function-to-lambda conversions and `extern "C"` wrapper generation. Third, `code-scribe translate` applies project-specific TOML-based few-shot prompt templates and submits the composed prompt to a pluggable LLM backend (OpenAI, Anthropic, Argonne ARGO, any OpenAI-compatible endpoint, or local Hugging Face checkpoints), producing a C++ source file, a header, and a Fortran-C++ interface file for each translated routine so the codebase compiles and runs correctly throughout the migration. Beyond translation, CodeScribe includes a tool-using coding agent (`code-scribe agent`) with read, bash, edit, and write capabilities, and a bounded loop mode (`code-scribe loop`) that runs repeated stateless agent sessions over a task file with restricted tool access — enabling sustained, auditable software development workflows for broader scientific computing tasks.

Dhruv, Akash [Argonne National Laboratory (ANL), A↗

Race conditions and data partitioning: risks posed by common errors to reproducible parallel simulations

When parallel algorithms for simulation were introduced in the 1970s, their development and use interested only experts in parallel computation. This circumstance changed as multi-core processors became commonplace, putting a parallel computer into the hands of every modeler. A natural outcome is growing interest in parallel simulation among persons not intimately familiar with parallel computing. At the same time, parallel simulation tools continue to be developed with the implicit assumption that the modeler is knowledgeable about parallel programming. The unintended consequence is a rapidly growing number of users of parallel simulation tools that are unlikely to recognize when the interaction of race conditions, partitioning strategies, and simultaneous action in their simulation models make results non-reproducible, thereby calling into question the validity of conclusions drawn from the simulation data. Here, we illustrate the potential dangers of exposing parallel algorithms to users who are not experts in parallel computation with example models constructed using existing parallel simulation tools. By doing so, we hope to refocus tool developers on usability, even if this new focus incurs loss of some performance.

97 MATHEMATICS AND COMPUTING↗

Mebendazole exhibits potent anti-leukemia activity on acute myeloid leukemia

Highlights: • MBZ inhibits the growth of AML cell lines while has little effect on normal PBMC. • MBZ induces mitotic arrest, mitotic catastrophe and apoptosis in AML cells. • MBZ treatment inhibits activation of Akt and Erk in AML cells. • MBZ demonstrates therapeutic efficacy in AML xenograft mouse model. Acute myeloid leukemia (AML) is one of the most common types of acute leukemia in adults with the lowest survival rate of all leukemia. Resistance to cytarabine and anthracycline-based chemotherapy is a major cause of treatment failure. Thus, finding new drugs with anti-leukemia activities and minimal side effect is urgently needed. Here through screening more than 1000 drugs approved by the Food and Drug Administration (FDA) of United States, the anthelmintic drug mebendazole (MBZ) was found to inhibit the growth of AML cell lines (THP-1, U937, NB4 and K562) and bone marrow mononuclear cells (BM-MNCs) from AML patients at pharmacologically achievable concentrations. In contrast, similar concentration of MBZ had little inhibitory effect on the growth of normal peripheral blood mononuclear cells (PBMC) or human umbilical vein endothelial cells (HUVEC). In addition, MBZ induced mitotic arrest and mitotic catastrophe in AML cells based on nuclear morphology, cell cycle distribution, mitotic marker analyses and the number of multinucleated cells and apoptotic cells. Furthermore, MBZ treatment inhibited activation of Akt and Erk in AML leukemic cells. Finally, MBZ repressed the progression of leukemic cells in vivo and prolonged survival in AML xenograft mouse model. Taken together, our results suggest that MBZ could be a potential new therapeutic agent for the treatment of AML patients.

60 APPLIED LIFE SCIENCES↗

RLC4CLR (Reinforcement Learning Controller for Critical Load Restoration Problems)

RLC4CLR demonstrates using a reinforcement learning controller (RLC) to solve a critical load restoration (CLR) problem, which improves the grid resilience after a substation outage event. RLC4CLR consists of two parts. (1) RL environment: This environment encapsulates the CLR problem to be solved and provides interfacing functions to follow the standard OpenAI Gym format. A power system simulator, i.e., OpenDSS, is included to provide the power flow solution. Controller inputs and outputs (RL state and action) as well as the reward are defined in this environment as well. In summary, the RL environment is the problem formulation from which the RL agent can learn. (2) RL training script: The training script enables the RL agent to learn its control policy by interacting with the RL environment. For RL training, an open-sourced RL library, i.e., RLlib, is leveraged which is based on a distributed computing framework (Ray). The training script is designed to be able to be run on both local machine or the NREL HPC system. Other components of RLC4CLR include input data, e.g., grid model (standard IEEE test feeders), and other files used for results analysis.

Zhang, Xiangyu↗

Intumescent coating modeling

A thermal response mathematical model for an intumescent coating system is developed. The model predicts indepth temperature profiles of the solid as a function of the fundamental kinetic, mass, and heat-transfer properties of the original coating system. In the model, swelling is based on an empirical function of the paint's weight loss. The model is used to describe the effectiveness of the coating for thermal protection. Using the thermal response time at the backface of the material as a criterion, a sensitivity analysis is made with respect to variation in individual properties, such as total expansion, to provide a guide for designing improved intumescing agents. The sensitivity analysis shows that total expansion and rate of expansion, along with other material properties, are important parameters for providing thermal protection. Finally, backface temperature histories are predicted and compared to experimental data obtained from a representative fire environment. Predicted temperatures agree within a maximum error of plus or minus 20%.

Cagliostro, D. E.↗

Adaptive Sensing of Time Series with Application to Remote Exploration

We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.

artificial intelligence↗

The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation

Abstract This work documents version two of the Department of Energy's Energy Exascale Earth System Model (E3SM). E3SMv2 is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid‐latitudes and 30 km at the equator and poles. The model performance is evaluated with Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate has many realistic features of the climate system, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3 K. In E3SMv2, ECS is reduced to 4.0 K which is now within the plausible range based on a recent World Climate Research Program assessment. However, a number of important biases remain including a weak Atlantic Meridional Overturning Circulation, deficiencies in the characteristics and spectral distribution of tropical atmospheric variability, and a significant underestimation of the observed warming in the second half of the historical period. An analysis of single‐forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol‐related forcing.

54 ENVIRONMENTAL SCIENCES↗

Impacts of anthropogenic gadolinium on the activity of the ammonia oxidizing bacterium Nitrosomonas europaea

Widespread use of gadolinium-based contrast agents in medical imaging has resulted in increased Gd inputs to municipal wastewater treatment plants. Others have reported that typical wastewater treatment does not attenuate Gd, resulting in discharges to natural waters. However, whether elevated Gd impacts the performance of biological treatment has not been investigated. We examined whether gadolinium chloride or Gd chelated with diethylenetriaminepentaacetic acid (DTPA) affected the activity of the model nitrifying bacterium Nitrosomonas europaea. At nominal GdCl 3 additions ranging from 1 to 500 µM, no impact was observed compared to the control. Most (>98%) of the added Gd precipitated, and extracellular GdPO 4 nanoparticles were observed. When chelated with DTPA, Gd remained soluble, but no statistically significant impact on ammonia oxidation was observed until the highest concentrations tested. At 300 and 500 µM Gd-DTPA, a temporary reduction of nitrite production relative to the control (effect size 1.3 mg l -1 and 1.5 mg l -1 , respectively, at 24 h) was seen. By itself, DTPA was highly inhibitory. Modeling suggested that DTPA likely chelated other metals, but adjusting the concentrations of the most abundant metals in the medium, calcium and magnesium, indicated that lowering their free ion activities was probably not the cause of inhibition. Complexation of other essential metals was more likely. Furthermore, our studies indicate that while the low bioavailability of Gd may limit its ecosystem impacts, the role of synthetic ligands used with Gd and other rare earth elements should e considered as the production, use and disposal of these elements increases.

54 ENVIRONMENTAL SCIENCES↗

Optimization-based approaches to control of connected and automated vehicles: Principles, complexities, applications, challenges, and outlook

Safe and optimal motion control for connected and automated vehicles (CAVs) poses a fundamental optimization challenge at the intersection of system complexity, environmental uncertainty, and stringent real-time constraints. Existing surveys address this challenge in isolation – focusing either on specific control techniques or individual uncertainty sources – without providing a unified framework that characterizes the trade-offs among computational tractability, performance verifiability, and adaptive generalization across paradigms. This review addresses that gap by presenting a cohesive analytical framework concentrated on the decision-making and trajectory optimization layers of the CAV autonomy stack. We systematically analyze three major optimization paradigms – first-principles model-based optimization, data-driven methods, and hybrid synergistic architectures – evaluating each against four core complexity axes: problem formulation, constraint handling, optimality guarantees, and robustness. Key applications including platooning, trajectory planning, collision avoidance, and cooperative control are examined to reveal recurring methodological patterns and critical operational constraints that limit real-world performance. Our synthesis identifies verifiable hybrid architectures, incentive-aligned multi-agent cooperation, and hardware-algorithm co-design as the defining research frontiers, and distills a targeted agenda for developing CAV control systems that are simultaneously safe, computationally efficient, and deployable in the full complexity of real-world traffic environments.

Muzahid, Abu Jafar Md [University of Tennessee, Kn↗

Suppression Characteristics of Cup-Burner Flames in Low Gravity

The structure and suppression of laminar methane-air co-flow diffusion flames formed on a cup burner have been studied experimentally and numerically using physically acting fire-extinguishing agents (CO2, N2, He, and Ar) in normal earth (lg) and zero gravity (0g). The computation uses a direct numerical simulation with detailed chemistry and radiative heat-loss models. An initial observation of the flame without agent was also made at the NASA Glenn 2.2-Second Drop Tower. An agent was introduced into a low-speed coflowing oxidizing stream by gradually replacing the air until extinguishment occurred under a fixed minimal fuel velocity. The suppression of cup-burner flames, which resemble real fires, occurred via a blowoff process (in which the flame base drifted downstream) rather than the global extinction phenomenon typical of counterflow diffusion flames. The computation revealed that the peak reactivity spot (the reaction kernel) formed in the flame base was responsible for attachment and blowoff phenomena of the trailing diffusion flame. The thermal and transport properties of the agents affected the flame extinguishment limits.

Takahashi, Fumiaki↗

Large-Scale Traveling Weather Systems in Mars Southern Extratropics

Between late fall and early spring, Mars' middle- and high-latitude atmosphere supports strong mean equator-to-pole temperature contrasts and an accompanying mean westerly polar vortex. Observations from both the MGS Thermal Emission Spectrometer (TES) and the MRO Mars Climate Sounder (MCS) indicate that a mean baroclinicity-barotropicity supports intense, large-scale eastward traveling weather systems (i.e., transient synoptic-period waves). Such extratropical weather disturbances are critical components of the global circulation as they serve as agents in the transport of heat and momentum, and generalized scalar/tracer quantities (e.g., atmospheric dust, water-vapor and ice clouds). The character of such traveling extratropical synoptic disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a moderately high-resolution Mars global climate model (Mars GCM). This Mars GCM imposes interactively-lifted and radiatively-active dust based on a threshold value of the surface stress. The model exhibits a reasonable "dust cycle" (i.e., globally averaged, a dustier atmosphere during southern spring and summer occurs). Compared to the northern-hemisphere counterparts, the southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense. Influences of the zonally asymmetric (i.e., east-west varying) topography on southern large-scale weather are investigated, in addition to large-scale up-slope/down-slope flows and the diurnal cycle. A southern storm zone in late winter and early spring presents in the western hemisphere via orographic influences from the Tharsis highlands, and the Argyre and Hellas impact basins. Geographically localized transient-wave activity diagnostics are constructed that illuminate dynamical differences amongst the simulations and these are presented.

Hollingsworth, Jeffery L.↗