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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

3D Play Fairway Analysis for Examining of Superhot Drilling Production Scenarios: Preprint

The DEEPEN (DE-risking Exploration for geothermal Plays in magmatic ENvironments) project was a multi-laboratory, international effort to reduce uncertainty and improve resource characterization in superhot geothermal systems. Building on this foundation, this work advances open-source tools designed to lower the exploration risk and cost of superhot geothermal projects while promoting transparency, reproducibility, and efficiency in exploration workflows. These tools are being tested at two key sites: (1) the Nesjavellir Geothermal Area in Iceland, where the Icelandic Deep Drilling Project (IDDP) will drill its third well, and (2) Newberry Volcano in Oregon, USA, where Mazama Energy will pilot the first superhot enhanced geothermal system (EGS). A major outcome is the creation of a modular, open-source Python framework for play fairway analysis (PFA) in 2D and 3D, called geoPFA. The PFA workflow has been expanded to produce pseudo conceptual models, and will soon be refined to assess reservoir components through integration with the thermo-hydraulic-mechanical-chemical (THMC) simulator TReactMech, to enable iterative coupling between PFA and THMC models, improving characterization of superhot systems. All three of the Icelandic Deep Drilling Project's production scenarios were analyzed via this framework: (1) a superhot deep injection well paired with conventional production wells at Nesjavellir, (2) a superhot deep production well at Nesjavellir, and (3) superhot enhanced geothermal system at Newberry Volcano. This analysis provides useful insights around conceptual modeling of these production scenarios, helping to inform decisions around which scenario is best suited for which types of environments.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Wireless Sensing and Communication Capability from In-Core to a Monitoring Center

Significant cost savings can be made if electrical cables can be replaced by wireless technology in current Nuclear Power Plants (NPP) and in advance reactor designs. Wireless technology can also provide in-core opportunities by significantly reducing the number of penetrations in the pressure vessel, cost and complexity of sensor installation and by increasing the efficiency of current and advanced reactors. Unlike other deployment scenarios for an industrial environment, operators need to have centralized control over all the networks. Centralized control will reduce implementation costs, provide single point control and enable monitoring of network devices, improve security, and enhance connectivity. Micro-sensors that can simultaneously monitor temperature and pressure within a fuel rod inside nuclear reactors will enable preventative actions during abnormal operating conditions. This ability could avert accidents and enable the expedient development of accident tolerant fuels. A novel micro-sensor suite (~ mm) to simultaneously measure multiple parameters such as temperature, strain, pressure, and neutron/gamma flux inside a fuel rod is being developed for use in reactors. The necessary communication architecture is also being developed to transmit measurement signals from the core to the plant's data cloud or control room. A three three-tier strategy has been developed to support wireless transmission of in-core measurements to the control room or to a secure cloud platform for control, analytics, and decision-making purposes. 1. In-core: data signal from in-core to outside of the pressure vessel within the containment building 2. Containment building: data signal from inside to the outside of the containment building and into the balance of the plant network 3. Balance of the plant network: information transmitted to the data cloud and control room This plan presents a wireless sensing and communication system for use within a reactor core and elsewhere. The communication technology is advantageous to compensate for network equipment failures and adverse data transmission conditions. Wireless technology will significantly increase the resiliency of the plants network system. The wireless system naturally provides multiple transmission path capability and data redundancy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Sustainable Electric Vehicle Batteries for a Sustainable World: Perspectives on Battery Cathodes, Environment, Supply Chain, Manufacturing, Life Cycle, and Policy

Abstract Li‐ion batteries (LIBs) can reduce carbon emissions by powering electric vehicles (EVs) and promoting renewable energy development with grid‐scale energy storage. However, LIB production and electricity generation still heavily rely on fossil fuels at present, resulting in major environmental concerns. Are LIBs as environmentally friendly and sustainable as expected at the current stage? In the past 5 years, a skyrocketing growth of the EV market has been witnessed. LIBs have garnered huge attention from academia, industry, government, non‐governmental organizations, investors, and the general public. Tremendous volumes of LIBs are already implemented in EVs today, with a continuing, exponential growth expected for the years to come. When LIBs reach their end‐of‐life in the next decades, what technologies can be in place to enable second‐life or recycling of batteries? Herein, life cycle assessment studies are examined to evaluate the environmental impact of LIBs, and EVs are compared with internal combustion engine vehicles regarding environmental sustainability. To provide a holistic view of the LIB development, this Perspective provides insights into materials development, manufacturing, recycling, legislation and policy, and beyond. Last but not least, the future development of LIBs and charging infrastructures in light of emerging technologies are envisioned.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Shallow Cumulus Entrainment Dynamics in a Sheared Environment

Abstract Vertical wind shear has long been known to tilt convective towers and reduce thermal ascent rates. The purpose of this study is to better understand the physical mechanisms responsible for reduced ascent rates in shallow convection. In particular, the study focuses on cloud-edge mass flux to assess how shear impacts mass-flux profiles of both the ensemble and individual clouds of various depths. A compositing algorithm is used to distill large-eddy simulation (LES) output to focus on up- and down-shear cloud edges that are not influenced by complex cloud geometry or nearby clouds. A direct entrainment algorithm is used to estimate the mass flux through the cloud surface. We find that the dynamics on the up- and down-shear sides are fundamentally different, with the entrainment of environmental momentum and dilution of buoyancy being primarily responsible for the reduced down-shear ascent rates. Direct estimates of fluid flow through the cloud interface indicate a counter-shear organized flow pattern that entrains on the down-shear side and detrains on the up-shear side, resulting from the subcloud shear being lifted into the cloud layer by the updraft. In spite of organized regions of entrainment and detrainment, the overall net lateral mass flux remains unchanged with respect to the no shear run, with weak detrainment present throughout cloud depth.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Evaluating software defined networking solutions to reduce the digital attack surface of nuclear security systems

Most nuclear security systems used today were not designed for today’s threat environment. Systems that were intended to be stand alone are now interconnected. Devices that have a single purpose are built on multi-purpose platforms and communication protocols that, while effective, have no ability to authenticate authorized versus unauthorized commands. These attributes provide an attacker significant ability to affect the system, pivot throughout the interconnected networks, and remain undetected if he/she is able to compromise a single node. Software defined networking (SDN) has been used for years by information technology (IT) cloud service providers to quickly provision or remove servers or other systems to meet changing demand. The same concept has recently been applied to operational technology (OT) systems to enable very fast failover on critical systems that have stringent and deterministic (<5ms) transmit/receive times. By carefully engineering the communication flows through a network using preplanned routes and specific pathways it is possible to achieve deterministic and extremely reliable message delivery even when components fail. This engineering approach to network design has added security benefits including securing the networking control plane, eliminating network scanning and mapping, inhibiting ARP spoofing and host masquerading, eliminating unauthorized network pivoting and enabling greater situational awareness on the network. SDN in OT environments is new but early testing in electrical power and other critical infrastructure has shown it to be a very powerful tool for building reliable networks and reducing the digital attack surface of the network. The authors tested a software defined network switch on a simple physical protection system with components commonly found in nuclear security systems and found improved mitigations to denial of service attacks, lateral movement and network reconnaissance. The paper details the tests and their results.

Cyber security, Nuclear security, software defined↗
DOE OSTI2026

Oxidation of biogenic U(IV) mediated by iron-bearing clay minerals, iron-reducing bacteria, and organic ligands

Bioreduction of hexavalent uranium (U(VI)) to tetravalent uranium (U(IV)) by dissimilatory metal-reducing bacteria (DMRB) is considered an effective strategy for uranium immobilization in contaminated environments. However, U(IV) can be reoxidized to U(VI) under fluctuating redox conditions and remobilized. This work investigates the oxidation behavior of biogenic U(IV) in the presence of bioreduced iron-bearing clay minerals (rNAu-2), iron-reducing bacteria (Shewanella putrefaciens CN32), and organic ligands (ethylenediaminetetraacetic acid (EDTA) and citrate). Results demonstrate that the presence of CN32 significantly inhibits U(IV) oxidation. rNAu-2 exerted a context-dependent influence on U(IV) oxidation: its effect was masked by bicarbonate-promoted U(VI) mobilization in the absence of active CN32, but became detectable when CN32-mediated microbial protection slowed U(IV) oxidation. EDTA and citrate markedly accelerate U(IV) oxidation via formation of soluble U(IV)-ligand complexes, changing U(IV) redox potentials, and by promoting clay mineral dissolution that enhances Fe(II)/Fe(III) redox cycling. Collectively, our findings constrain the roles that clay minerals, iron-reducing bacteria, and organic ligands play in governing U(IV) stability, emphasizing the need to account for these factors in developing robust bioremediation strategies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Optimization of Conditions for Photoluminescence-Based Sensing of Critical Minerals: Strategies and Outlook

Economically critical minerals and metals are vital to America’s security, with application areas in energy, advanced technologies, and defense systems. The growing implementation of renewable energy sources such as electric vehicles is expected to significantly increase demand for these minerals, while the global supply is monopolistic, with most of the production occurring in a few countries outside of the US. To mitigate potential supply chain vulnerabilities, the domestic production of economically critical metals has become a bipartisan priority of the US government, and unconventional sources such as coal and its utilization byproducts such as fly ash and acid mine drainage are being actively explored as an alternative method for meeting domestic demand. Slow and expensive characterization methods for critical metals present a significant pain point for domestic production, which has led to the exploration of alternative low-cost, portable platforms capable of detecting target metals during resource prospecting and downstream process monitoring. The National Energy Technology Laboratory has developed a portable fiber optic-based luminescence spectrometer that utilizes a metal-organic framework (MOF) material to detect and distinguish parts-per-billion levels of the visible-emitting rare earth elements terbium, dysprosium, samarium, and europium, which are all economically critical metals. Although preliminary results with this system are promising, a crucial barrier to practical deployment is the ability to operate in low pH, high ionic strength environments, as acidic conditions and the presence of other metal ions can significantly reduce luminescence signal. Here, current strategies related to sample treatment, material design, and sensor configuration are discussed in the context of improving sensor performance in application-relevant conditions. Additionally, future opportunities, such as the optimization of the sensing binding environment through computational methods and specific metals to be removed for treatment will be discussed, presenting a forward-looking view for innovation in luminescent sensing of critical metals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Heterogeneous Machine Learning on High Performance Computing for End to End Driving of Autonomous Vehicles

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving. For machines though, this gap is guarded by at least two challenges: 1) machine learning techniques remain brittle and unable to generalize to a wide range of scenarios, and 2) effective training data that enhances generalization and generates the desired driving behavior. Further, each challenge can be computationally intensive on its own thereby exasperating the gap. Moreover, is has not yet been shown that a single form of learning or training is capable of addressing a large range of scenarios. As a result, solving the first challenge does not inherently solve the second and vice versa. The work described here discusses an approach to address the first challenge that would also provide a foundation for solving the second. Our approach utilizes a combination of conditional imitation learning with a static dataset, reinforcement learning with a simulation environment, and high-performance computing to train a neural network. As a result, this reduces the “time to solution” from to the existing techniques for autonomous driving and provides an extensible framework to address the second key challenge.

autonomous vehicles↗
DOE OSTI2024

Machine learning for reducing noise in RF control signals at industrial accelerators

Industrial particle accelerators typically operate in dirtier environments than research accelerators, leading to increased noise in RF and electronic systems. Furthermore, given that industrial accelerators are mass produced, less attention is given to optimizing the performance of individual systems. As a result, industrial accelerators tend to underperform their own hardware capabilities. Improving signal processing for these machines will improve cost and time margins for deployment, helping to meet the growing demand for accelerators for medical sterilization, food irradiation, cancer treatment, and imaging. Our work focuses on using machine learning techniques to reduce noise in RF signals used for pulse-to-pulse feedback in industrial accelerators. Here we review our algorithms and observed results for simulated RF systems, and discuss next steps with the ultimate goal of deployment on industrial systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Piecewise Linear Optimization for Public EV Charging Depots in Different Utility Environments

With the proliferation of electric vehicles (EVs), EV supply equipment technology is being pushed to increasingly higher power levels, such as extreme fast charging (XFC) at 300kW or more. As more public XFC depots are connected to electric distribution systems, utility operators will mitigate their impact with pricing schemes and programs such as demand response, demand charges, and time-varying prices. In this paper we describe an XFC management system that combines an on-site battery energy storage system and an optimization application that minimizes the cost to operate the depot in light of the utility pricing programs. We have designed the optimizer specially to use fast and simple linear programming so that it can be deployed to low-cost computing platforms. We also describe how several utility pricing schemes are integrated into a single piecewise model, reducing the engineering effort to implement the optimizer in different utility environments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Characterization of Interconnects

Combined-accelerated stress testing (C-AST) simultaneously combines stress factors of the natural environment (including UV radiation, temperature, humidity, electrical current, and external mechanical force) into a single test that requires fewer modules, fewer chambers, and makes it possible to discover weaknesses in new designs that are not known a-priori. C-AST reduces risk, accelerates time to market, and improves bankability by reducing costly overdesign using test levels not exceeding those seen in the natural environment. This project seeks to evaluate strengths and weaknesses of modern cell interconnect designs with combined-accelerated stress testing (C-AST) to screen multiple climates along with finite element and failure analysis to determine the potential for a 50-year life. Supporting this, we seek to develop methods of characterization to assess the degradation of interconnects, enable predictive rate models with material forensics and FEA and show C-AST's ability to find interconnect failures and benchmark it relative to other accelerated stress test methods like temperature cycling and cyclic dynamic mechanical loading. Examples of modern interconnect designs covered are Canadian Solar Hetero Technology ribbon enabling closer cell interconnections, SmartWire (eg. Meyer-Berger technology), and shingled cells with new interconnect materials.

C-AST↗
DOE OSTI2022

Oceanographic Conditions. 2007 - 2040. North Slope Alaska.

Complete representations of oceanographic conditions require spatial and temporal information about the significant wave height (Hs), peak wave period (Tp), wind speed, wind direction, wave direction, water level, salinity, and temperature. This data develops location-independent typologies to reduce the number of boundary conditions needed to assess nearshore oceanographic environments in both a Historical (2007-2019) and Future (2020-2040) timespan along the Alaskan North Slope. Wave information for both time spans were generated from WaveWatch III, Delft3D-FLOW, and Delft3D-WAVE simulations forced by wind conditions from reanalysis data (e.g., ASRv2 and ERA5) for the historical simulations while projected conditions were obtained from downscaled GFDL-CM3 forced under RCP8.5 conditions. Salinity was generated from GOFS 3.1 for the years between 2008-2015 and skin temperature of the ocean was obtained from ASRv2 reanalysis data for the years between 2007-2016. To identify generalized oceanographic typologies, K-means clustering was applied to the energy-weighted joint-probability distribution of Hs and Tp at six sites along the North Slope of Alaska. Distributions of wave and wind direction, wind speed, and water level associated with locaiton-indepndent centroids were assigned single values to describe a reduced order, typological rendition of offshore oceanographic conditions. These final typologies and their constituent data are provided here and can be used to evaluate the change in ocean energy over the next two decades in response to climate change and provide insight into expected consequences such as coastal erosion and flooding. A full assessment of the findings and techniques developed can be found in: Eymold, W.K., Flanary, C., Erikson, L., Nederhoff, K., Chartrand, C.C., Jones, C., Kasper, J., and Bull, D.L. Typological Representation of the Offshore Oceanographic Environment along the Alaskan North Slope. Continental Shelf Research (2022). 10.1016/j.csr.2022.104795

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Pathways to commercial building plug and process load efficiency and control

Abstract To accomplish net-zero carbon emissions in the built environment by 2050, we must equitably decarbonize commercial buildings, including reducing plug and process loads (PPLs). PPLs are plug-in or hardwired electric and gas loads that are not associated with major building end uses like lighting and HVAC. Research shows PPL energy reduction strategies and control technologies have the potential to save energy. But even when implemented, these savings have rarely been achieved and there has not been widespread uptake in U.S. commercial buildings. We investigate why these technologies and strategies have not seen widespread adoption and identify behavior and technology pathways to increase PPL reduction in U.S. commercial buildings. We examined behaviors of commercial building stakeholders through 44 interviews and cross-referenced qualitative analysis findings with in-depth technical knowledge of existing PPL control technologies and reduction strategies. PPL control implementation must be paired with management strategies, such as occupant engagement and training, to achieve optimal savings, and best practices should be disseminated across the industry. We found that increasing access to cost and energy savings data will promote uptake of PPL control technologies and allow designers to better incorporate PPLs into building design. Improving access to funding for PPL energy efficiency projects and addressing the split-incentive problem will increase adoption of PPL efficiency and control. Code bodies should continue to include PPL monitoring and reduction measures in energy codes. Key building stakeholders, including cybersecurity and information technology teams, should be involved in PPL monitoring and reduction strategy processes for successful implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Using temperature and flow fields to detect gas leakage from canisters containing spent nuclear fuel: Applications to RAMM-TM

The multi-physics STAR-CCM+ code has been used to simulate the temperature and flow fields in canister gas leakage experiments conducted by using a 1/4.5-scale model storage cask. The simulations were conducted at Argonne National Laboratory’s Laboratory Computing Resource Center, utilizing high-performance computing resources. Development of STAR-CCM+ simulation models for the 1/4.5-scale model cask is described herein, followed by validation of the simulation results against experimental data. Canister depressurization and thermal response during gas leakage are discussed, along with analyses of the leakage path and allowable leakage rate. The insights gained from the STAR-CCM+ simulations and leakage analyses will help guide future experiments and actual industry applications of Argonne’s Remote Area Modular Monitoring system for canister surface temperature measurement (RAMM-TM) to enable effective aging management of spent fuel during extended dry storage, as well as help reduce risks to public safety and health and protect the environment.

Canister gas leakage↗
DOE OSTI2023

Metallic Cation-Mediated Entrapment of Nucleic Acids on Mesoporous Silica Surface: Application in Castration-Resistant Prostate Cancer

The use of exogenous nucleic acid technologies to modulate aberrant protein expression resulting from genetic mutations is a promising therapeutic approach for the treatment of diseases such as advanced prostate cancer (PC). The promise of nucleic-based therapeutics is dependent on the development of platforms that effectively protect nucleic acids from nuclease degradation and deliver the nucleic acids to the cytosol of target cells. In this work, we present the development of a divalent metal-mediated nucleic acid entrapment strategy with a porous silica matrix. This simple strategy results in efficient loading percentages of both siRNA (>60%) and mRNA (>80%) as well as their release within relevant biological environments (80%). Additionally, our data supports that the current method reduces endosomal entrapment and supports the lipid coating of mesoporous silica nanoparticles (LC-MSNs). Finally, the metal-enhanced nanosystem is assessed for biocompatibility, stability, and circulation within in vitro, ex ovo, and in vivo models of PC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Experimental evolution reveals nitrate tolerance mechanisms in Desulfovibrio vulgaris

Elevated nitrate in the environment inhibits sulfate reduction by important microorganisms of sulfate-reducing bacteria (SRB). Several SRB may respire nitrate to survive under elevated nitrate, but how SRB that lack nitrate reductase survive to elevated nitrate remains elusive. To understand nitrate adaptation mechanisms, we evolved 12 populations of a model SRB (i.e., Desulfovibrio vulgaris Hildenborough, DvH) under elevated NaNO 3 for 1000 generations, analyzed growth and acquired mutations, and linked their genotypes with phenotypes. Nitrate-evolved (EN) populations significantly (p < 0.05) increased nitrate tolerance, and whole-genome resequencing identified 119 new mutations in 44 genes of 12 EN populations, among which six functional gene groups were discovered with high mutation frequencies at the population level. In this work, we observed a high frequency of nonsense or frameshift mutations in nitrosative stress response genes (NSR: DVU2543, DVU2547, and DVU2548), nitrogen regulatory protein C family genes (NRC: DVU2394-2396, DVU2402, and DVU2405), and nitrate cluster (DVU0246-0249 and DVU0251). Mutagenesis analysis confirmed that loss-of-functions of NRC and NSR increased nitrate tolerance. Also, functional gene groups involved in fatty acid synthesis, iron regulation, and two-component system (LytR/LytS) known to be responsive to multiple stresses, had a high frequency of missense mutations. Additionally, mutations in those gene groups could increase nitrate tolerance through regulating energy metabolism, barring entry of nitrate into cells, altering cell membrane characteristics, or conferring growth advantages at the stationary phase. This study advances our understanding of nitrate tolerance mechanisms and has important implications for linking genotypes with phenotypes in DvH.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Ligand-coordinated Ir single-atom catalysts stabilized on oxide supports for ethylene hydrogenation and their evolution under a reductive atmosphere

In this work, we present a novel series of oxide-supported Ir-ligand single-atom catalysts (SACs) for ethylene hydrogenation. The SACs were created by a metal–ligand self-assembly strategy developed by our group, using one of two ligands, either 1,10-phenanthroline-5,6-dione (PDO) or 3,6-Di-2-pyridyl-1,2,4,5-tetrazine (DPTZ), on powder supports of either CeO 2 or MgO. Characterization by XAS, XPS, and CO adsorption proved that Ir exist principally as highly uniform, cationic single-atoms. Ir SACs show significantly higher durability and metal utilization efficiency than Ir nanoparticle (NP) catalysts during ethylene hydrogenation at 100 °C, as well as excellent stability, as no Ir aggregates were detected after >10 h reaction. The activity can be tuned by ligand and support effects: PDO and CeO 2 are superior to DPTZ and MgO, respectively. This tunability is attributed to differences in H 2 activation capability, which results from differences in support reducibility, electron density on Ir, and, potentially, the local coordination environment of Ir. The Ir SACs lose H 2 activation activity either under inert gas or under H 2 . Through XPS and in situ XAS studies, we attributed the former to the reversible loss of Ir hydride, which is the active species for H 2 activation, and the latter to irreversible over-hydrogenation and loss of Ir–O/N coordination. This work presents a new type of Ir hydrogenation SACs that are more durable, efficient, and tunable than supported Ir NPs, while more stable than homogeneous Ir complexes. It also offers fundamental understanding regarding ligand and support effects, as well as the evolution of Ir single-atoms under H 2 , instructing future design of stable, effective hydrogenation SACs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

In recent years, there has been a growing trend toward the development of smart buildings that rely on cyber-physical systems (CPS) to optimize occupant comfort, safety, and energy efficiency. To ensure the reliable and efficient operation of CPS with designed control strategies, it is important to evaluate their performance under various scenarios before deploying them in the real world. This is where a Hardware-in-the-loop (HIL) testbed designed for studying sensor and control-related studies in smart buildings can be highly valuable. With the growing threat of cyber-attacks and physical faults targeting smart buildings, it is essential to ensure the security of building operations. A HIL testbed can emulate cyber-attack and physical fault scenarios, allowing researchers to develop and test threat detection and mitigation algorithms. This enables researchers to identify potential issues and optimize the algorithms in a safe and controlled environment before they are deployed in real-world settings, reducing the risk of failures that can negatively impact occupant comfort, safety, and energy efficiency. Therefore, this paper developed a HIL testbed designed for cyber-physical energy systems (e.g. buildings automation system (BAS)) in smart commercial buildings. The HIL testbed is comprised of a real-time building and Heating, Ventilation, and Air-Conditioning (HVAC) emulator using Modelica-based dynamic models, a set of BAS controllers, and a BAS computer server. The data generation capability of the HIL testbed is demonstrated by tracking normal and faulty operating data in the BAS, as well as monitoring detailed network traffic in the local BAS network. Here, this study further demonstrates the HIL testbed’s capability by conducting case studies on real-time physical fault and cyber-attack experiments using a Department of Energy (DOE) prototype commercial building. It is anticipated that the fully functional HIL testbed will be utilized for a variety of sensor and control-related studies, including but not limited to testing, developing, validating of different HVAC control strategies, fault detection & diagnosis, energy monitoring and analysis, cyber security study, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗