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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Controlled dehumidification to extract clean water from a multicomponent gaseous mixture of organic contaminants

Rapid expansion of the unconventional oil and gas extraction has increased American energy independence, but also led to increased production of large amounts of contaminated water. Wastewater from the oil and gas industry contains a wide range of contaminants. Injecting such contaminated water into disposal wells or discharging it to the environment jeopardizes freshwater resources. Conventional and membrane-based wastewater treatment techniques are often not effective choices to treat highly contaminated wastewater; however, a suitable way to remove contaminants from wastewater is to selectively separate water in a process analogous to humidification-dehumidification (HDH). Only a few studies have investigated the use of HDH for wastewater treatment. In this study, a novel HDH system is introduced for treating highly contaminated water, such as oil and gas flowback and produced water. In this HDH process, a non-condensable gas, such as air, mixes with wastewater vapor to facilitate the separation of contaminants. As a result, clean water condenses from the multicomponent gaseous mixture while air carries organic contaminants out of the dehumidification section. A laboratory apparatus was constructed and experiments were performed to investigate the HDH process for wastewater treatment and to study the effects of flow dynamics including air flow rate on the composition of treated water. Different contaminants including benzene, toluene, 2-propanol and 2-butoxyethanol were tested. Experimental results showed that the system can be successfully applied for removing volatile and/or toxic organic contaminants from wastewater. A representative multicomponent mixture of fracking wastewater was successfully treated using the experimental setup and clean water with quality of 98.3% was obtained. It was revealed that increasing the air-to-vapor mass ratio improves purity of treated water. Quantitative analysis showed that by increasing the air-to-vapor mass ratio from 0.6 to 5.9, the fraction of separated 2-propanol through the air was improved from 43% to more than 96% of the initial amount. ASPEN software was employed to simulate equilibrium conditions. Finally, experimental results were observed to have lower mass fraction of residual contaminant in the treated water compared to equilibrium state.

42 ENGINEERING↗
DOE OSTI2020

Devising novel methods for the controlled synthesis with morphology and size control of scintillator materials

Nanoscale scintillators represent an important class of materials underlying the functioning of high resolution, high ‘light yield’ radiation detection equipment, applicable for medicine in addition to security and environmental monitoring. This current study has focused on the controlled synthesis of Cs 2 ZnX 4 (X = Cl, Br) not only due to its very fast and promising radioluminescence decay time but also because no reliable synthesis protocols have been reported for producing nanoscale motifs of this material, to date. Solution-based methods can be used to synthesize products, possessing different, discrete morphologies with the ability to dictate particle size and shape. Specifically, we have demonstrated that a hot injection technique can be used to fabricate nanoscale rods and plates. Using this method, we systematically studied the effect of varying reaction variables, such as (i) reaction temperature, (ii) surfactants, and (iii) reaction time. As synthesized nanorods of Cs 2 ZnCl 4 possessed lengths of 101.3 ± 24.4 nm with widths of 17.3 ± 4.5 nm, whereas Cs 2 ZnBr 4 , created under identical conditions, were characterized by lengths of 206 ± 50 nm and widths of 26.7 ± 12.6 nm. Ligand-assisted re-precipitation (LARP) was used to produce the corresponding micron-sized particles. Under these conditions, we successfully synthesized spindles and spherical particles of Cs 2 ZnCl 4 with sizes of 1.58 ± 0.16 μm and 1.03 ± 0.34 μm, respectively, whereas plates of Cs 2 ZnBr 4 were prepared with average sizes of 0.76 ± 0.21 μm. High resolution synchrotron mapping, using the hard X-ray nanoprobe at NSLS II, was used to confirm the expected spatial distribution of Cs, Zn, and Cl within the as-produced crystals. Nanorods of Cs 2 ZnCl 4 and Cs 2 ZnBr 4 were subsequently tested for scintillation light yield and decay times. Preliminary results showed that Cs 2 ZnCl 4 maintained a light yield of 100–300 photons per MeV with a fast decay component of 2.6 ns. Finally, the Cs 2 ZnBr 4 analogue did not give rise to any perceptible scintillation emission.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A dynamic solvent chamber propagation estimation framework using RNN for warm solvent injection in heterogeneous reservoirs

Warm solvent injection (WSI), injecting low-temperature solvent into formations to reduce the viscosity of heavy oil, is a clean technology for heavy oil production through reducing greenhouse gas emissions and water usage. The success of WSI operation depends on the uniform development and propagation of solvent chambers in reservoirs. However, reservoir heterogeneity stemming from shale barriers plays a detrimental role in the conformance of solvent chamber development and oil production rate. In this work, we developed a novel recurrent neural network (RNN)-based framework with the capability of efficiently tracking and estimating the solvent chamber positions in heterogeneous reservoirs based on only production time-series data. The developed estimation model utilizes the “sequence-to-sequence" mapping methodology to correlate observed production time-series sequence and solvent chamber edge sequence via a long short-term memory (LSTM) algorithm. The trained RNN models exhibit high accuracy, evidenced by the predicted dynamic solvent chamber locations match the corresponding true locations from numerical simulation, with a high coefficient of determination (R 2 ) and a low mean squared error. Specifically, the achieved R 2 values exceed 0.98 on both the training and testing data. The developed RNN-based workflow was tested via several cases from both regularly- and irregularly-shaped shale barriers, and the results were promising. The predicted solvent chambers showed strong agreement with those obtained from numerical simulations. The major benefits of this workflow include reducing computational time and saving overall monitoring and tracking costs for conventional techniques. In conclusion, the present work would provide a good demonstration of the capability of practical integration of machine learning methods in solving engineering problems.

58 GEOSCIENCES↗
DOE OSTI2025

Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learning

Modern vehicles rely on a myriad of electronic control units (ECUs) interconnected via controller area networks (CANs) for critical operations. Despite their ubiquitous use and reliability, CANs are susceptible to sophisticated cyberattacks, particularly masquerade attacks, which inject false data that mimic legitimate messages at the expected frequency. These attacks pose severe risks such as unintended acceleration, brake deactivation, and rogue steering. Traditional intrusion detection systems (IDS) often struggle to detect these subtle intrusions due to their seamless integration into normal traffic. This paper introduces a novel framework for detecting masquerade attacks in the CAN bus using graph machine learning (ML). We hypothesize that the integration of shallow graph embeddings with time series features derived from CAN frames enhances the detection of masquerade attacks. We show that by representing CAN bus frames as message sequence graphs (MSGs) and enriching each node with contextual statistical attributes from time series, we can enhance detection capabilities across various attack patterns compared to using graph-based features only. Our method ensures a comprehensive and dynamic analysis of CAN frame interactions, improving robustness and efficiency. Extensive experiments on the ROAD dataset validate the effectiveness of our approach, demonstrating statistically significant improvements in the detection rates of masquerade attacks compared to a baseline that uses graph-based features only as confirmed by Mann-Whitney U and Kolmogorov-Smirnov tests (p < 0.05) .

Marfo, William [Univ. of Texas, El Paso, TX (Unite↗
DOE OSTI2023

Stacked Greenfield and Brownfield ROZ Fairways in the Illinois Basin Geo-Laboratory: Co-Optimization of EOR and Associated CO 2 Storage

Residual oil zones (ROZs) are economically viable targets for carbon dioxide enhanced oil recovery (CO 2 -EOR); thick, carbonate ROZs in the San Andres Formation in the Wasson Field of the Permian Basin are an example. Incremental oil produced from CO 2 -EOR can be carbon negative via associated storage of injected CO 2 . Given the regional extent of ROZ fairways and generally higher net utilization of CO 2 (compared to conventional CO 2 -EOR), ROZs provide the opportunity for significant carbon neutral to carbon negative oil production with associated CO 2 storage, and therefore should be a priority target for exploration. However, ROZs have not been widely recognized or identified due to poor or no conventional oil production. Hence, in places like the Illinois Basin (ILB), exploratory analyses are required to recognize the existence of an ROZ. As part of this study, four formations were selected for detailed regional characterization and analysis: Carper Sandstone (part of the Borden Siltstone), Tar Springs Sandstone, Cypress Sandstone, and Middle Devonian (Geneva Dolomite and associated Dutch Creek Sandstone). The four formations underwent regional geological characterization to develop a regional geologic framework for the ROZs and their overlying seals. Findings of this study are supported by data from two field laboratory sites, one with stacked greenfield ROZs and the other with a stacked complex that includes a brownfield ROZ and depleted conventional reservoirs. The field laboratory sites were used to collect data and conduct tests to validate ROZ detection methodologies and identify economic field-deployable strategies to co-optimize CO 2 -EOR and associated storage in stacked ROZs. Findings from these field sites were extrapolated to characterize the basin-wide stacked ROZ fairway resource.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Software-defined network for end-to-end networked science at the exascale

Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work presented here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end- to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Software-Defined Network for End-to-end Networked Science at the Exascale

Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work we presen here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end-to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Design of a Continuous Pellet Fueling System for Wendelstein 7-X

A continuous pellet fueling system (CPFS) is currently being designed at the Oak Ridge National Laboratory (ORNL) for the long pulse operation of the Wendelstein 7-X (W7-X) stellarator. The purpose of the CPFS is to provide deep continuous fueling for feedback-controlled high-density operation and mitigation of predicted hollow density profiles. As described here, the system will provide the capability to inject cylindrical pellets of solid hydrogen or deuterium into the plasma core, with flexibility to vary the pellet size, velocity, and injection frequency. Pellets are nominally of 3 mm in diameter and have a length between 1 and 4 mm. The heart of the CPFS is a vertically oriented, twin-screw extruder, cooled by three Gifford-McMahon cryocoolers in parallel, designed to form a continuous filament of hydrogen or deuterium. The filament width, which determines the pellet length, can be adjusted by means of a variable nozzle driven by a linear actuator at the base of the extruder. Coupled to the nozzle is a solenoid-operated gas gun and cutter assembly. A pneumatic propellant valve pulses a burst of ~60 bar helium to accelerate the cut pellet into W7-X. Three gaps in the guide tubes provide pumping locations to remove the helium propellant before it reaches the plasma. The maximum velocity of the pellet is limited by its ability to survive navigating the guide tube trajectory intact. A microwave cavity located within the guide tube provides the capability to measure the pellet size and velocity. The mechanical and thermal designs of the W7-X extruder, adjustable nozzle, and gun and cutter assembly design are described. A guide tube design and experimental pellet survivability test results are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Mechanical Design of the PIP-II ORBUMP Pulsed Dipole Magnet

The Proton Improvement Plan II (PIP-II) project is a vital upgrade to the Fermilab accelerator complex. The magnet pulse rate of the PIP-II Injection system requires an increase from the current rate of 15 Hz to 20 Hz as well as a roughly 30% increase in the magnetic field of the new Orbital Bump (ORBUMP) pulsed dipole magnets in the Booster. Here, the ORBUMP magnet mechanical design is presented in this paper. The ORBUMP magnet is secured in a vacuum box and the core is made up of 0.127 mm thick, low carbon steel laminations with a C-5 inorganic magnesium phosphate coating. The core is clamped using external tie bars welded to the core end plates. ANSYS Finite Element Analysis (FEA) was used to evaluate the clamping design to minimize the deflection of the core post welding of the tie bars. The water-cooled, single turn coil, which shapes the magnetic field by acting as the pole tips, is critical for the integrated field homogeneity. The coil manufacturing tolerances and fabrication techniques were evaluated to ensure the magnetic properties of the magnet could be obtained. The coil is electrically isolated from the core using virgin Polyether ether ketone (PEEK) insulating material in the gap. An investigation into the high voltage performance of the virgin PEEK insulator was conducted via partial discharge testing using a 1:1 scale sample.

Karas, D. [Fermi National Accelerator Laboratory (↗
DOE OSTI2023

The effect of gas injection location on a lithium vapor box divertor in NSTX-U

Abstract The lithium vapor box divertor is a proposed divertor design that will minimize contamination of the upstream plasma in a fusion device, while also ensuring protection of the target. In this design lithium is evaporated near the target by high temperature lithium surfaces, dissipating the plasma heat flux. The lithium vapor box has been predicted via the fluid-kinetic code scrape off layer plasma simulator (SOLPS-ITER) to achieve low ( n L i / n e ∼ 0.05) upstream concentrations of lithium and low target heat fluxes. Here we compare two choices of deuterium gas puff location using SOLPS-ITER, the private flux region (PFR) and the common flux region (CFR), and find significant differences in the contamination level required to reach an acceptable target heat flux (defined here as q tar max ⩽ 10 MW m −2 ). Deuterium gas puffing from the PFR is seen to better reduce upstream lithium contamination. The difference in puffing location is seen to cause changes in the upstream flow of lithium ions. The PFR puff, having better access to the separatrix, can better reduce the upstream-directed flow of lithium near the separatrix which is the primary source of contamination due to a large thermal force in this region. Puffing from the CFR, partially due to inefficacy at reducing separatrix lithium flow, has higher lithium concentration within the plasma. Solutions that reduce the heat flux to below 10 MW m −2 have a range of lithium concentrations between n L i / n e ∼ 0.01–0.12 depending on puff intensity, location, evaporator temperature and recycling at the various plasma facing components. The efficacy of the puffs is tested for sensitivity to deuterium recycling coefficient at the target, evaporators, and main chamber walls. A CFR located puff is found to be more dependent on the recycling coefficients used than a PFR located puff. regardless of the set of recycling coefficients chosen, PFR puffing achieves lower lithium contamination than CFR puffing for a given heat flux.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Memory forensic analysis of a programmable logic controller in industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLCs) are used to automate physical processes such as nuclear plants and power grid stations, and are often subject to cyber attacks. As in conventional IT domain, the memory analysis of the PLCs can help answer important forensic questions about the attack, such as the presence of malicious firmware, injection of modified control logic (the program running on the PLC), and manipulation of I/O devices (e.g., sensors and actuators). Unlike conventional IT domain, PLCs have heterogeneous hardware architecture, proprietary firmware and control software, making it challenging to employ a unified framework for their memory forensics. For merely extracting artifacts of forensic importance, reverse-engineering the firmware is a tedious task, and the effort needs to be repeated for every PLC model. As a community, a step-wise approach to tackle this challenge is to analyze the memory of specific PLCs, and subsequently find a generic framework applicable to all PLCs. Our work is a step forward in this direction. By following a methodology that focuses on the functional layer of PLCs instead of reverse engineering the firmware, we analyze the digital forensic artifacts available in a common PLC, Allen-Bradley ControlLogix 1756-L61. Before diving into the memory dump, we analyze the PLC control software to create a list of important artifacts that are sure to exist in the PLC memory dump. The approach employs a setup where PLC control software RSLogix-5000 is connected to the PLC, and the memory dump can be obtained as and when needed. We create test cases that sequentially highlight each category of artifacts, followed by an examination of the resultant impact on memory. After attaining the listed artifacts, we employ conventional string and known data searches to extract interesting information present in this PLC's memory. The memory analysis profile, presented as a Python library and shared with the community, can help a forensic investigator to readily extract forensic artifacts from the same model's controller. The adopted approach may help researchers in creating memory profile of other PLCs, and ultimately formulating a generic PLC memory analysis framework.

Rais, Muhammad Haris↗
DOE OSTI2020

Effect of Computational Schemes on Coupled Flow and Geo-Mechanical Modeling of CO 2 Leakage through a Compromised Well

Carbon capture, utilization, and storage (CCUS) describes a set of technically viable processes to separate carbon dioxide (CO 2 ) from industrial byproduct streams and inject it into deep geologic formations for long-term storage. Legacy wells located within the spatial domain of new injection and production activities represent potential pathways for fluids (i.e., CO 2 and aqueous phase) to leak through compromised components (e.g., through fractures or micro-annulus pathways). The finite element (FE) method is a well-established numerical approach to simulate the coupling between multi-phase fluid flow and solid phase deformation interactions that occur in a compromised well system. We assumed the spatial domain consists of a three-phases system: a solid, liquid, and gas phase. For flow in the two fluids phases, we considered two sets of primary variables: the first considering capillary pressure and gas pressure (PP) scheme, and the second considering liquid pressure and gas saturation (PS) scheme. Fluid phases were coupled with the solid phase using the full coupling (i.e., monolithic coupling) and iterative coupling (i.e., sequential coupling) approaches. The challenge of achieving numerical stability in the coupled formulation in heterogeneous media was addressed using the mass lumping and the upwinding techniques. Numerical results were compared with three benchmark problems to assess the performance of coupled FE solutions: 1D Terzaghi’s consolidation, Liakopoulos experiments, and the Kueper and Frind experiments. We found good agreement between our results and the three benchmark problems. For the Kueper and Frind test, the PP scheme successfully captured the observed experimental response of the non-aqueous phase infiltration, in contrast to the PS scheme. These exercises demonstrate the importance of fluid phase primary variable selection for heterogeneous porous media. We then applied the developed model to the hypothetical case of leakage along a compromised well representing a heterogeneous media. Considering the mass lumping and the upwinding techniques, both the monotonic and the sequential coupling provided identical results, but mass lumping was needed to avoid numerical instabilities in the sequential coupling. Additionally, in the monolithic coupling, the magnitude of primary variables in the coupled solution without mass lumping and the upwinding is higher, which is essential for the risk-based analyses.

deformation flow↗
DOE OSTI2020

Geologic Characterization for CO 2 Storage with Enhanced Oil Recovery in Northern Michigan

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. This report compiles the results of geologic characterization of late-stage reefs, active EOR reefs, and new EOR reefs in the Northern Niagaran Pinnacle Reef Trend (NNPRT) in Michigan to demonstrate developed methodologies, geologic variability, and reservoir potential for CO 2 storage. Conducting CO 2 injection and monitoring in these settings provide significant insights for addressing the project objectives: assessment of injectivity in complex carbonate reef deposits; assessing CO 2 trapping mechanisms in a closed reservoir system; assessing any final oil recovery from transitional or residual oil zones in a field where CO 2 flooding is nearing completion; evaluating the transition from EOR to storage of CO 2 ; assessing regional commercialization; assessing new technologies for tracking CO 2 , brine, and oil movements underground; and monitoring options in a closed reservoir with oil, residual oil, and water zones.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Assessment and Simulation of Particulate Transport for Delivery of Solid Amendments into the Subsurface: FY25 Status Report

For particulate-based amendments to be viable for field-scale remediation at the Hanford Site (e.g., the 200 DV-1 Operable Unit), amendment particles need to be delivered a reasonable distance away from an injection well to provide cost effective in situ treatment. Field-scale particle transport models can estimate spatial deposition of amendment particles in the subsurface, which is critical for developing an overall remediation strategy. However, field-scale particle simulations are currently limited due to insufficient simulation capability and a lack of experimental data to validate and parameterize particle transport models. During this fiscal year, the following progress has been made toward a field-scale particle transport modeling evaluation: (1) in addition to the two particle transport models implemented last FY, four additional particle transport models have been implemented within PFLOTRAN; (2) a Python-based pre-screening tool was finalized, enabling users to quickly estimate the particle radius of influence (ROI) for any given particle-amendment system; and (3) an initial compatibility assessment was completed using both particle transport simulations deployed through the pre-screening tool, in conjunction with general guidelines to (a) identify the most suitable amendment particle sizes for various Hanford sediments and (b) evaluate amendment-delivery fluid compatibility. The preliminary compatibility assessment revealed that for amendment delivery success to the various Hanford target formations, amendment particle sizes will likely need to be smaller than the amendment sizes tested in the DV-1 treatability study. It is recommended that amendment particles be decreased in size, or alternative smaller size amendments be obtained from the manufacture, prior to any further experimental testing. Also, preliminary testing suggests that xanthan gum may be the most broadly compatible delivery fluid. Planned laboratory experiments will be instrumental in validating and refining the PFLOTRAN particulate transport model formulations, ultimately enabling predictive capabilities to facilitate the design of field-scale amendment delivery systems. This work consists of acquiring new theoretical or experimental knowledge. The information associated with this report should not be used as design input or operating parameters without additional qualification.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Advanced Transmission Technologies – GETs and HPCs Session 2: Advanced Power Flow Control and Transmission Topology Optimization

The INL TADA GETs Cohort Session 2, held on November 7, 2025, conducted in collaboration with ScottMadden, focused on two core Advanced Transmission Technologies (ATTs): Advanced Power Flow Control (APFC) and Transmission Topology Optimization (TTO). These technologies are pivotal in enhancing grid flexibility, reliability, and cybersecurity resilience. APFC, particularly through modular FACTS devices like Modular Static Synchronous Series Compensators (M-SSSCs), enables dynamic voltage injection to reroute power flows. The session highlighted the deployment benefits of APFC, such as rapid installation, minimal civil works, and re-deployability. Regulatory drivers like FERC Order 2023 mandate the inclusion of Grid-Enhancing Technologies (GETs) in interconnection studies. Case studies from Central Hudson, CAISO, and National Grid (UK) demonstrated APFC’s effectiveness in congestion relief and cost savings. The session also addressed cybersecurity concerns, including firmware vulnerabilities, SCADA integration risks, and supply chain dependencies. Participants engaged in interactive exercises to rank cybersecurity and supply chain risks, emphasizing the need for robust digital assurance strategies. TTO involves software-based reconfiguration of transmission networks to optimize power flow without new infrastructure. The session showcased its operational value, with examples from SPP, PJM, and MISO showing significant congestion cost reductions. Cybersecurity vulnerabilities were discussed, particularly in API security and software supply chains, referencing incidents like SolarWinds and attacks on Danish utilities. Digital assurance exercises explored worst-case scenarios, attack paths, and mitigation responsibilities between vendors and utilities. Reliability challenges such as algorithm stability, vendor dependency, and operator trust were also examined. Cross-cutting themes emphasized the importance of digital assurance tools, including Software Bills of Materials (SBOMs) and hardware-in-loop testing. Human performance, training, and operational confidence were identified as critical enablers of technology adoption. The session concluded with a preview of Session 3, which will focus on High Performance Conductors (HPCs) and risk-based cybersecurity tools. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A data-driven sensor placement approach for detecting voltage violations in distribution systems

Stochastic fluctuations in power injections from distributed energy resources (DERs) combined with load variability can cause constraint violations (e.g., exceeded voltage limits) in electric distribution systems. To monitor grid operations, sensors are placed to measure important quantities such as the voltage magnitudes. Here, in this paper, we consider a sensor placement problem which seeks to identify locations for installing sensors that can capture all possible violations of voltage magnitude limits. We formulate a bilevel optimization problem that minimizes the number of sensors and avoids false sensor alarms in the upper level while ensuring detection of any voltage violations in the lower level. This problem is challenging due to the nonlinearity of the power flow equations and the presence of binary variables. Accordingly, we employ recently developed conservative linear approximations of the power flow equations that overestimate or underestimate the voltage magnitudes. By replacing the nonlinear power flow equations with conservative linear approximations, we can ensure that the resulting sensor locations and thresholds are sufficient to identify any constraint violations. Additionally, we apply various problem reformulations to significantly improve computational tractability while simultaneously ensuring an appropriate placement of sensors. Lastly, we improve the quality of the results via an approximate gradient descent method that adjusts the sensor thresholds. We demonstrate the effectiveness of our proposed method for several test cases, including a system with multiple switching configurations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2022

An Innovative Zero-Liquid Discharge Intermediate-Cold-Liquid Eutectic-Freeze Desalination System

A novel freeze desalination technology is presented for purification of water produced from various industrial processes, including oil and gas extraction. The main innovative idea is introducing a water-immiscible intermediate-cold-liquid (ICL) medium which absorbs the cold from a refrigeration cycle and transfers it to a freezing chamber where it is mixed with brine. The cold ICL enters the freezing chamber at temperatures between -10°C to -30°C. Precooled brine in injected into the freezing chamber and pure water freezes out of the brine upon mixing with the ICL. The rate of freezing inside the chamber is controlled by adjusting the flow rate of the cold ICL relative to the inlet brine. Both eutectic freeze and non-eutectic freezing are possible by controlling the temperature of the freezing chamber. The solid-liquid slurry created in the freezing chamber flows to a filter separation unit after passing through a separation column. The ice crystals are separated from the liquid by a rotary filter device. The collected ice is rinsed by a centrifugal unit. The rinsed ice is melted to produce fresh water. The developed technology resolves the issues common to current freeze-desalination systems while offering superior heat transfer performance ascribed to direct-contact between the cooling medium and the brine in addition to producing solid salt and pure water. The system operates under atmospheric pressure. The low operation temperature minimizes the corrosion issues common in systems exposed to brine. Also, due to the low operating temperature, there are no concerns about evaporation of volatile organics from the produced water during the treatment. The developed technology effectively eliminates the use of chemicals for pretreatment of brine. The system can be constructed from commercially available components. Extensive testing using a lab-scale prototype by using synthetic brine and actual produced water with TDS values from 50,000 ppm to 300,000 ppm showed that freshwater could be achieved with relatively small dependency on the quality of the input brine. The quality of the treated water was found to be mainly a function of the duration of the centrifugal process. Treated water with TDS as low as 200 ppm could be achieved in the tests. Thermo-economic modeling coupled with system level thermochemical process model were developed for prediction of the LCOW. The LCOW was predicted to be $\$$0.50 to $\$$0.90 per barrel of produced water. The potential markets for deployment of the technology are the oil and gas, in-land thermoelectric powerplants, RO desalination plants, and mining industry.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗