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At least 1,117 records · Page 62

BrickQA: Bridging the Semantic Gap in Building Operations with Dynamic Graph Exploration

While standardized ontologies like the Brick schema address data heterogeneity in Building Automation Systems (BAS), accessing this semantic data remains a challenge as domain experts often lack the expertise to formulate complex SPARQL queries. To bridge this gap, we present BrickQA, a Large Language Model (LLM)-based framework that translates natural language into executable SPARQL queries through structured query decomposition, dynamic schema exploration, and inline validation. BrickQA utilizes an iterative reasoning agent to actively navigate graph topology through dynamic exploration actions without requiring exhaustive context injection or model fine-tuning. This approach effectively mitigates hallucinations, particularly in large-scale building knowledge graphs. Empirical evaluation on BuildingQA, a standardized benchmark, demonstrates that BrickQA significantly outperforms ReAct baselines, delivering a 0.291–0.355 absolute F1 improvement while achieving 3 × –12.7 × higher token cost-efficiency. Beyond these metrics, the framework maintains structural fidelity across heterogeneous buildings and remains resilient to ambiguous queries without requiring site-specific fine-tuning. Furthermore, a case study on operational analytics validates the framework’s capability to handle temporal and aggregation constraints, effectively transforming abstract semantic models into actionable facility management insights.1

Ko, Yun-Dam↗

AI-Based Faster-Than-Real-Time Stability Assessment of Large Power Systems with Applications on WECC System

Achieving clean energy goals will require significant advances in regard to addressing the computational needs for next-generation renewable-dominated power grids. One critical obstacle that lies in the way of transitioning today’s power grid to a renewable-dominated power grid is the lack of a faster-than-real-time stability assessment technology for operating a fast-changing power grid. This paper proposes an artificial intelligence (AI) -based method that predicts the system’s stability margin information (e.g., the frequency nadir in the frequency stability assessment and the critical clearing time (CCT) value in the transient stability assessment) directly from the system operating conditions without performing the conventional time-consuming time-domain simulations over detailed dynamic models. Since the AI method shifts the majority of the computational burden to offline training, the online evaluation is extremely fast. This paper has tested the AI-based stability assessment method using multiple dispatch cases that are converted and tuned from actual dispatch cases of the Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. The results show that the AI-based method could accurately predict the stability margin of such a large power system in less than 0.2 milliseconds using the offline-trained AI agent. Therefore, the proposed method has great potential to achieve faster-than-real-time stability assessment for practical large power systems while preserving sufficient accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Model-based Executive Control through Reactive Planning for Autonomous Rovers

This paper reports on the design and implementation of a real-time executive for a mobile rover that uses a model-based, declarative approach. The control system is based on the Intelligent Distributed Execution Architecture (IDEA), an approach to planning and execution that provides a unified representational and computational framework for an autonomous agent. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting agents, each with the same fundamental structure. We show that planning and real-time response are compatible if the executive minimizes the size of the planning problem. We detail the implementation of this approach on an exploration rover (Gromit an RWI ATRV Junior at NASA Ames) presenting different IDEA controllers of the same domain and comparing them with more classical approaches. We demonstrate that the approach is scalable to complex coordination of functional modules needed for autonomous navigation and exploration.

Finzi, Alberto↗

Creating an Interface to view Multi-Spacecraft Swarm Telemetry

Distributed Spacecraft Systems are a type of multi-spacecraft mission architecture that can not only provide improved resolution, coverage, and availability of existing missions, but also enable missions that would be previously infeasible using traditional approaches. Distributed Spacecraft Autonomy (DSA) is a project developed by the National Aeronautics and Space Administration that enables distributed spacecraft systems. In previous science swarm missions, the spacecraft involved have not been able to communicate with each other without utilizing a ground station. Now that the spacecraft can perform inter-satellite communication, the spacecraft can be treated as a collective. Swarm autonomy is critical for a growing number of satellites which means novel ways of displaying swarm data needs to be implemented. Such systems introduce unique challenges to traditional approaches for command and control of these spacecraft, due to the large number of spacecraft and the complexity of the interactions between them. The ground data system for DSA addresses these challenges through the creation of a custom user interface that allows a single operator to orchestrate a multi-spacecraft swarm in a scalable way. This plenary describes the details of the autonomy demonstration being performed, the requirements of those using the interface to analyze the spacecraft telemetry to assess demonstration success, and the approach taken by the ground systems team to create an interface that satisfies these requirements. This approach involves the creation of several distinct components that correspond to the level of detail presented to the user. These components are based on conventional user roles in human-robot interaction, including supervisor, operator, and mechanic, extended to accommodate the additional overhead of coordinating actions between agents. One main feature of the interface is the listenability matrix component which will represent inter-satellite communications in a heat mapped matrix. The above work described will enable users to command and interact with the spacecraft as a collective.

human-swarm interaction↗

Organoammonium-Ion-based Perovskites Can Degrade to Pb 0 via Amine–Pb(II) Coordination

The degradation of alkylammonium Pb II halide perovskites, in the dark and upon irradiation near room temperature, involves coordinated amine as the dominant reducing agent to yield Pb o near room temperature, as determined by X-ray photoelectron spectroscopy (XPS). The reduction of Pb II first involves amine coordination, supported by 207 Pb nuclear magnetic resonance (NMR) analysis. It is shown that a Pb II –amide complex is the immediate precursor of Pb II reduction. Its oxidized counterpart, the imine, is formed and is characterized by NMR and gas chromatography–mass spectrometry. Here, the “redox” process requires a β-C–H bond of the alkylamine. Amine species devoid of this moiety do not similarly reduce Pb II to Pb o . The conversion of an alkylammonium moiety to the Pb II –amide is proposed to occur through a sequence of photoassisted proton-transfer reactions to a lead-coordinated ligand, which is substantiated through XPS-observed Pb II reduction in a family of lead bromide/iodide 2D perovskites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temporal and Resource Reasoning for Planning, Scheduling and Execution in Autonomous Agents

This viewgraph slide tutorial reviews methods for planning and scheduling events. The presentation reviews several methods and uses several examples of scheduling events for the successful and timely completion of the overall plan. Using constraint based models the presentation reviews planning with time, time representations in problem solving and resource reasoning.

Muscettola, Nicola↗

Haughton-Mars Project Expedition 2005

The 2005 expedition to the Haughton-Mars Project (HMP) research station on Devon Island was part of a NASA-funded project on Space Logistics. A team of nine r&searchers from MIT went to the Canadian Arctic to participate in the annual I-IMP field campaign from July 8 to August 12, 2005. We investigated the applicability of the HMP research station as an analogue for planetary macro- and micro-logistics to the Moon and Mars, and began collecting data for modeling purposes. We also tested new technologies and procedures to enhance the ability of humans and robots to jointly explore remote environments. The expedition had four main objectives. We briefly summarize our key findings in each of these areas. 1. Classes of Supply: First, we wanted to understand what supply items existed at the HMP research station in support of planetary science and exploration research at and around the Haughton Crater. We also wanted to quantify the total amount of imported mass at HMP and compare this with predictions from existing parametric lunar base demand models. 2. Macro-Logistics Transportation Network: Our second objective was to understand the nodes, transportation routes, vehicles, capacities and crew and cargo mass flow rates required to support the HMP logistics network. 3. Agent and Asset Tracking: Since the current inventory management system on ISS relies heavily on barcodes and manual tracking, we wanted to test new automated technologies and procedures such as radio frequency identification RFID) to support exploration logistics. 4. Micro-Logistics (EVA): Finally, we wanted to understand the micro-logistical requirements of conducting both short (<1 day) and long traverses in the Mars-analog terrain on Devon Island. Micro-logistics involves the movement of surface vehicles, people and supplies from base to various exploration sites over short distances (<100 km).

deWeck, Olivier↗

Optimal carbon storage reservoir management through deep reinforcement learning

Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decision-making problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Finally, experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.

15 GEOTHERMAL ENERGY↗

Reasoning abstractly about resources

r describes a way to schedule high level activities before distributing them across multiple rovers in order to coordinate the resultant use of shared resources regardless of how each rover decides how to perform its activities. We present an algorithm for summarizing the metric resource requirements of an abstract activity based n the resource usages of its potential refinements.

abstraction planning rovers multiple agents↗

Sorption and Desorption Study of a Nerve-Agent Simulant from Office Materials for Forensic Applications

Dimethyl methylphosphonate (DMMP) was used as a simulant to investigate the sorption and desorption of G-series nerve agents such as sarin (GB) released into an office space. DMMP was disseminated systematically as an aerosol and vapor on three common office materials, cardboard, polyurethane foam, and cured acrylic-based paint. The amount of DMMP initially captured on the office materials and the amount retained over a period of 10 hours was tracked gravimetrically and by solvent extraction and gas chromatography/mass spectrometry (GC/MS). Physicochemical properties of the office media including the specific surface area per mass, polarity, and Henry’s constants were determined to help explain the capture and release of DMMP that was observed. Polyurethane foam was found to have the largest sorption capacity for DMMP in a low-humidity setting, however, cardboard was found to have the largest sorption capacity at higher humidity. A fraction of the DMMP collected desorbed with first-order kinetics from all of the office materials in an open-air atmosphere over 8 hours. However, importantly for forensic purposes relevant to an indoor attack, a significant quantity (most notably on cardboard) of the nerve agent simulant was retained after 6 weeks and could be analyzed efficiently using solvent extraction followed by GC/MS.

chemical forensics↗

Carbon-Based Multi-Phase Rotating Detonation Engine

Abstract This article focuses on extending an H2/air rotating detonation engine's detonability limits by introducing solid carbon particles into the combustor. Carbon black particles consisting of 1% volatility and a carbon concentration of 99% were used as a solid-phase mixing agent for enhanced reaction wave dynamics. Carbon black was found to sustain detonations over multiple operational regimes formerly unattainable without carbon particles. The experiments confirm that detonations were attainable over a wide range of operational parameters, including the total mass flux flowing through the annulus (≅120–270 kg/s m2), the hydrogen/air equivalence ratios (0.65–1.0), and carbon additions (0–20 g). Chemiluminescence imaging was used to visualize the detonation wave within the annulus, quantify detonation wave velocities, and define a detonability map. The detonability map demonstrates the advantage of carbon addition, shows that detonation-based combustion can be sustained at leaner equivalence ratios, reduces hydrogen consumption dependency. The detonation wave velocities decreased as the H2/air equivalence ratio was reduced, where, in general, the detonation wave velocities decreased with respect to the Chapman–Jouguet velocity, suggesting a decrease in the detonation waves efficiency with reduced H2 concentrations. However, an extraordinary phenomenon was witnessed at very lean H2/air equivalence ratios and low mass flux conditions, where the detonation wave velocity increased upward of 100 m/s. This variation is a direct effect of the carbon particles, which drive the detonation wave. Thus, the results demonstrate that carbon particles’ addition provides an economically feasible solution to sustain high-efficiency energy production.

Energy & Fuels↗

Evaluating the Adaptability of Reinforcement Learning Based HVAC Control for Residential Houses

Intelligent Heating, Ventilation, and Air Conditioning (HVAC) control using deep reinforcement learning (DRL) has recently gained a lot of attention due to its ability to optimally control the complex behavior of the HVAC system. However, more exploration is needed on understanding the adaptability challenges that the DRL agent could face during the deployment phase. Using online learning for such applications is not realistic due to the long learning period and likely poor comfort control during the learning process. Alternatively, DRL can be pre-trained using a building model prior to deployment. However, developing an accurate building model for every house and deploying a pre-trained DRL model for HVAC control would not be cost-effective. In this study, we focus on evaluating the ability of DRL-based HVAC control to provide cost savings when pre-trained on one building model and deployed on different house models with varying user comforts. We observed around 30% of cost reduction by pre-trained model over baseline when validated in a simulation environment and achieved up to 21% cost reduction when deployed in the real house. This finding provides experimental evidence that the pre-trained DRL has the potential to adapt to different house environments and comfort settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Effect of Al{sub 2}O{sub 3}/(B{sub 2}O{sub 3 }+ Na{sub 2}O) Ratio on CaO-Al{sub 2}O{sub 3}-Based Mold Fluxes: Melting Property, Viscosity, Heat Transfer, and Structure

CaO-Al{sub 2}O{sub 3}-based mold fluxes, which are under development for the continuous casting of high-Al steel, contain fluxing compounds, such as Na{sub 2}O and B{sub 2}O{sub 3}. The reaction between [Al] and the fluxing agents in mold fluxes leads to an increase in Al{sub 2}O{sub 3} and a decrease in B{sub 2}O{sub 3} and Na{sub 2}O concentrations, changing the properties of mold fluxes. The effect of the Al{sub 2}O{sub 3}/(B{sub 2}O{sub 3 }+ Na{sub 2}O) ratio on the melting properties, viscosity, heat transfer, and structure of the CaO-Al{sub 2}O{sub 3}-based mold fluxes is presented in this work. The increase of the Al{sub 2}O{sub 3}/(B{sub 2}O{sub 3 }+ Na{sub 2}O) ratio in the fluxes raised the melting temperature and high-temperature viscosity of mold fluxes but decreased the heat transfer rate across the flux disks. It also enhanced the degree of polymerization by promoting the formation of 3-D aluminate structure, which accounted for the change of the viscous behavior.

36 MATERIALS SCIENCE↗

Prebiotic phosphorylation of nucleosides in formamide

Results are presented for an experimental study intended to assess phosphorylation under neither aqueous nor dry thermal conditions. Instead, phosphorylations were attempted in possible nonaqueous prebiotic solvents. Formamide appeared to be the most obvious candidate for phosphorylation studies. Three main classes of phosphorylated products were formed in formamide solution: adenosine monophosphates, cyclic adenosine phosphate, and adenosine diphosphates. Experiments were designed to investigate the extent of phosphorylation of nucleosides in formamide, the relative amounts of nucleoside monophosphate, diphosphates and cyclic phosphate formed and the relative effectiveness of different sources of phosphate as phosphorylating agents in formamide. Reaction variables were temperature, nature of the phosphate or condensed phosphate, nucleoside, concentration of reactants and possible effects of additives. Product identification was based on qualitative and quantitative thin layer chromatography.

Schoffstall, A. M.↗

Crop-phenology and LANDSAT-based irrigated lands inventory in the high plains

Crop calendars for 1979 and 1980 were investigated in support of an effort to develop techniques for mapping the High Plains aquifer region. Optimal LANDSAT image dates for 1980 were preliminarily identified based on ESS weekly crop weather reports and 1979 ESS agricultural statistics were entered into the computer. A questionnaire was compiled and sent to ASCS county agents with the approval of the Extension Directors in each state involved. Data from returning questionnaires were tabulated and development started on a set of computer programs to allow the preparation of computer assisted graphic displays of much of the collected data.

Martinko, E. A.↗

Compact Apparatus Grows Protein Crystals

Laboratory apparatus provides delicately balanced combination of materials and chemical conditions for growth of protein crystals. Apparatus and technique for growth based on hanging-drop method for crystallization of macromolecules. Includes pair of syringes with ganged plungers. One syringe contains protein solution; other contains precipitating-agent solution. Syringes intrude into cavity lined with porous reservoir material saturated with 1 mL or more of similar precipitating-agent solution. Prior to activation, ends of syringes plugged to prevent transport of water vapor among three solutions.

Bugg, Charles E.↗

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.↗

Modeling Space Radiation with Radiomimetic Agent Bleomycin

Space radiation consists of proton and helium from solar particle events (SPE) and high energy heavy ions from galactic cosmic ray (GCR). This mixture of radiation with particles at different energy levels has different effects on biological systems. Currently, majority studies of radiation effects on human were based on single-source radiation due to the limitation of available method to model effects of space radiation on living organisms. While NASA Space Radiation Laboratory is working on advanced switches to make it possible to have a mixed field radiation with particles of different energies, the radiation source will be limited. Development of an easily available experimental model for studying effects of mixed field radiation could greatly speed up our progress in our understanding the molecular mechanisms of damage and responses from exposure to space radiation, and facilitate the discovery of protection and countermeasures against space radiation, which is critical for the mission to Mars. Bleomycin, a radiomimetic agent, has been widely used to study radiation induced DNA damage and cellular responses. Previously, bleomycin was often compared to low low Linear Energy Transfer (LET) gamma radiation without defined characteristics. Our recent work demonstrated that bleomycin could induce complex clustered DNA damage in human fibroblasts that is similar to DNA damage induced by high LET radiation. These type of DNA damage is difficult to repair and can be visualized by gamma-H2Ax staining weeks after the initial insult. The survival ratio between early and late plating of human fibroblasts after bleomycin treatment is between low LET and high LET radiation. Our results suggest that bleomycin induces DNA damage and other cellular stresses resembling those resulted from mixed field radiation with both low and high LET particles. We hypothesize that bleomycin could be used to mimic space radiation in biological systems. Potential advantages and limitations of using bleomycin to treat biological specimen as an easily available model to study effects of space radiation on biological systems and to develop countermeasures for space radiation associated risks will be discussed.

Lu, Tao↗