Multi-Agent Partial Observable Safe Reinforcement Learning for Counter Uncrewed Aerial Systems
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42 ENGINEERING↗
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A safe reinforcement learning algorithm for supervisory control of power plants
Traditional control theory-based methods require tailored engineering for each system and constant fine-tuning. In power plant control, one often needs to obtain a precise representation of the system dynamics and carefully design the control scheme accordingly. Model-free Reinforcement learning (RL) has emerged as a promising solution for control tasks due to its ability to learn from trial-and-error interactions with the environment. It eliminates the need for explicitly modeling the environment’s dynamics, which is potentially inaccurate. However, the direct imposition of state constraints in power plant control raises challenges for standard RL methods. To address this, we propose a chance-constrained RL algorithm based on Proximal Policy Optimization for supervisory control. Our method employs Lagrangian relaxation to convert the constrained optimization problem into an unconstrained objective, where trainable Lagrange multipliers enforce the state constraints. In conclusion, our approach achieves the smallest distance of violation and violation rate in a load-follow maneuver for an advanced Nuclear Power Plant design.
constrained optimization↗
The ATWS analysis of the HTR-10GT core induced by the earthquake - 18489
The 10 MW High Temperature Gas Cooled Test Reactor (HTR-10) has been built in Institute of Nuclear and New Energy Technology (INET) and has been operating successfully since the beginning of 2003. The core outlet temperature of HTR-10 is 700 deg. C. To verify the technology of gas-turbine direct cycle, at first INET had a plan to increase its core outlet temperature to 750 deg. C and use a helium gas turbine instead of the steam generator (then the reactor is called HTR-10GT). Though HTR-10 has good intrinsic safety, the design basic accidents and beyond design basis accidents of HTR-10GT must be analyzed according to China s nuclear regulations due to changed operation parameters. THERMIX code system is used to study the Anticipated Transient Without Scram (ATWS) caused by an earthquake. The gravity acceleration of the earthquake will make the porosity of the pebble bed smaller, which will thus induce a positive reactivity. The packing fraction of the HTR-10GT core will increase to 0.64 from 0.61, while a reactivity of 1.24% will be inserted into an initial core and 0.788% for an equilibrium core. Then the reactor power increased and the temperature of the core increased. When the neutron flux of power measuring range exceeded 123% and the reactor period becomes less than 20 seconds, the reactor should scram. It was supposed that all the control rods in the reflectors had been blocked and the reactor could not scram. Thus the accident went on and the core temperature and the system pressure increased but the reactor shutdown at last because of its natural negative temperature reactivity feedback mechanism. The residual heat would be removed out of the core by the cavity cooling system. During the accident sequence the maximum fuel temperature was 1223 deg. C. If a temperature coefficient error of 20% was considered during analyzing, the peak temperature of the fuel during the ATWS will reach 1266 deg. C. It was a little higher than 1230 deg. C --the fuel temperature limitation of HTR-10. Now the sphere fuel used in HTR-10GT will also be used in HTR-PM and the temperature limitation has been raised to 1620 deg. C, so the HTR-10GT is safe during the ATWS caused by an earthquake. The paper also compares the analysis result of HTR10-GT to those of HTR-10. The results shows that the HTR-10GT is still safe during the accident though its operating temperature is higher than HTR-10. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Origin and regulation of oxygen redox instability in high-voltage battery cathodes
Oxygen redox at high-voltage has emerged as a transformative paradigm for high-energy battery cathodes such as layered transition-metal oxides by offering extra capacity beyond conventional transition-metal redox. However, these cathodes suffer from voltage hysteresis, voltage fade, and capacity drop upon cycling; single-crystalline cathodes have recently shown some improvements but these challenges still remain. We reveal the fundamental origin of oxygen redox instability to be originated from the domain boundaries that are present in single-crystalline cathode particles. By synthesizing single-crystalline cathodes free of domain boundaries, we show that the elimination of domain boundaries enhances the reversible lattice oxygen redox while inhibiting the irreversible oxygen release. Further, this leads to significantly suppressed structural degradation and improved mechanical integrity during battery cycling and abuse heating. The robust oxygen redox enabled through domain boundary control provides practical opportunities towards high-energy, long-cycling, and safe batteries.
25 ENERGY STORAGE↗
Low-Cost III-V Photovoltaic Materials by Chloride Vapor Transport Deposition Using Safe Solid Precursors
Si-based photovoltaic devices dominate the market. As photovoltaic (PV) manufacturing costs have plummeted, technologies which increase efficiency have become critical. Si cell efficiencies are nearing theoretical limits and Si-based PV modules are unlikely to reach the 25-30% efficiency range. The use of III-V semiconductors is an obvious technical solution to improve efficiency, especially if they can be integrated directly with existing Si technology as tandems. High coefficients of light absorption along with tunable bandgaps and lattice constants have resulted in record conversion efficiencies for both one-sun and concentrator PV applications. GaAs, for example, has been used to manufacture single-junction photovoltaics with world-record efficiencies of 28.8% at one sun.2 However, costs for III-Vs must be dramatically reduced to produce cost-effective, high-efficiency PV solutions. III-V costs are controlled by two factors: semiconductor growth and the substrate. III-V growth is dominated today by metal-organic vapor phase epitaxy (MOVPE) with a lesser role played by molecular beam epitaxy (MBE). MOVPE costs are high due to the expense and low utilization (~30%) of precursors, modest growth rates (~100 nm min -1 ), equipment complexity, and safety infrastructure needed to handle toxic, pyrophoric gases.3 MBE costs are high due to slow growth rates and limitations of scalability. Details comparing plausible low-cost III-V growth methods are available in a review article published as a result of this project. The primary goal of this project was to demonstrate that close-spaced vapor transport (CSVT) using chloride (from HCl) as a transport agent can be used for the rapid growth of device-ready III-V layers from safe, solid-source precursors. In pursuit of this goal, we designed, built, and installed a new Cl-CSVT reactor based on insights from our previous H 2 O-CSVT growth system and in collaboration with equipment professionals at Malachite Technologies. This system was successfully used to grow epitaxial GaAs with controlled n-type doping, having mobilities similar to MOVPE. Detailed technical information and results can also be found in the primary publication resulting from this project. This work sets the stage for tackling the development of high-performance III-V single junctions and tandem devices directly on Si substrates, which was beyond the capabilities of our H2O-CSVT system. The design of the reactor’s source and substrate transfer system should allow for direct deposition of device structures. The collective innovations of our Cl-CSVT system might ultimately serve as an enabling process for commercialization of the technology through a collaboration with appropriate industrial partners.
14 SOLAR ENERGY↗
COVID 19 vaccine distribution solution to the last mile challenge: Experimental and simulation studies of ultra-low temperature refrigeration system
Most COVID-19 vaccines require ambient temperature control for transportation and storage. Both Pfizer and Moderna vaccines are based on mRNA and lipid nanoparticles requiring low temperature storage. The Pfizer vaccine requires ultra-low temperature storage (between -80 °C and -60 °C), while the Moderna vaccine requires -30 °C storage. Pfizer has designed a reusable package for transportation and storage that can keep the vaccine at the target temperature for 10 days. However, the last stage of distribution is quite challenging, especially for rural or suburban areas, where local towns, pharmacy chains and hospitals may not have the infrastructure required to store the vaccine. Also, the need for a large amount of ultra-low temperature refrigeration equipment in a short time period creates tremendous pressure on the equipment suppliers. In addition, there is limited data available to address ancillary challenges of the distribution framework for both transportation and storage stages. As such, there is a need for a quick, effective, secure, and safe solution to mitigate the challenges faced by vaccine distribution logistics. The study proposes an effective, secure, and safe ultra-low temperature refrigeration solution to resolve the vaccine distribution last mile challenge. Furthermore, the approach is to utilize commercially available products, such as refrigeration container units, and retrofit them to meet the vaccine storage temperature requirement. Both experimental and simulation studies are conducted to evaluate the technical merits of this solution with the ability to control temperature at -30 °C or -70 °C as part of the last mile supply chain for vaccine candidates.
60 APPLIED LIFE SCIENCES↗
Transhepatic Tract Embolisation After Biliary Intervention Using n-Butyl Cyanoacrylate and Autologous Blood: A Retrospective Analysis of 42 Patients
Purpose: We evaluated the safety and efficacy of transhepatic tract embolisation after a biliary intervention using n-butyl cyanoacrylate (NBCA) and autologous blood. Materials and Methods: Between January 2017 and December 2018, 42 consecutive patients (mean age: 71 ± 15 years, 24 men) with malignant (n = 26) or benign (n = 16) biliary obstructions underwent percutaneous biliary intervention followed by tract embolisation within 2 weeks. Forty-six transhepatic tracts (4 bilateral) in 42 patients were embolised using a NBCA and lipiodol mixtures (1:1–1:2 ratios) after intraductal infusion of peripherally obtained autologous blood. The indwelling catheter diameters were 8.5–14 Fr. The median interval between percutaneous biliary drainage and tract embolisation was 10 days (range 3–14 days). Glue-cast formation via fluoroscopy and immediate complications were reviewed retrospectively in medical records. Follow-up data (median: 135, range 11–720 days) including computed tomography (CT) images (n = 17) were evaluated for delayed complications and glue-cast formation. Results: Successful glue-cast formations were achieved in all 46 tracts. No patients experienced haemorrhage, and only one patient had external bile leakage. Eight patients complained of abdominal pain (numerical scale ≤ 5) immediately after embolisation, which was controlled by analgesics. Two patients had transient fever. Segmental (n = 11) or sub-segmental (n = 6) glue-cast patterns were identified along the transhepatic tract by follow-up CT. No biliary obstructions were caused by inadvertent glue spread. Fragmented glue was detected outside the stent in one patient. Conclusion: Transhepatic parenchymal tract embolisation with NBCA and autologous blood is a safe and feasible method for preventing bile leakage. Level of Evidence: Level 4, Case Series.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Titanium Carbide MXene Shows an Electrochemical Anomaly in Water-in-Salt Electrolytes
Identifying and understanding charge storage mechanisms is important for advancing energy storage. Well-separated peaks in cyclic voltammograms (CVs) are considered key indicators of diffusion-controlled electrochemical processes with distinct Faradaic charge transfer. Herein, we report on an electrochemical system with separated CV peaks, accompanied by surface-controlled partial charge transfer, in 2D Ti 3 C 2 T x MXene in water-in-salt electrolytes. The process involves the insertion/desertion of desolvation-free cations, leading to an abrupt change of the interlayer spacing between MXene sheets. This unusual behavior increases charge storage at positive potentials, thereby increasing the amount of energy stored. This also demonstrates opportunities for the development of high-rate aqueous energy storage devices and electrochemical actuators using safe and inexpensive aqueous electrolytes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Right Transfer Access Control Model of Internet of Things Based on Smart Contract
Sensor nodes play a crucial role in the promotion of development of Internet of Things (IoT). Through this transaction, RO defines access control policies in script form based on ABAC's access control model to grant access right. The identity of all users in the model is identified by address. This paper builds a more flexible right transfer access control model by means of combining the Attribute-Based Access Control model (ABAC) and blockchain technology. Owing to the characteristics of ABAC’s attributes and right association, the massive problems of some sensor nodes can be solved. At the same time, for the sake of addressing the dynamic problems such as node access and right transfer, right transfer contract (TS) and access control contract (CS) are employed on the chain to ensure efficient and safe transmission of rights. To solve on-chain storage problems and ensure transparency of the operation, the idea of Rollup in Ethereum expansion is used to upload the final state of protocol policy and right exchange to the chain. Any user can know the policy and current right transfer status at any time. Finally, comparative and security analysis show that the model presented here can solve IoT devices’ massive and dynamic problems more effectively and it is more secure than the traditional models.
Wang, Jiuru↗
Teleoperation for Nuclear Applications Considering Communication Delay and Uncertainty - 18205
Teleoperation in remote environment is of great interest in robotics. Advancement in communication technology has enabled safe execution of complex and life threatening tasks in network environment in teleoperation. Using bilateral teleoperation, the operator receives force feedback from the slave which provides an interactive feel of forces and smoother coordination. However, time delay across the communication link in sending the command signal from the master to the slave may cause instability to the system. In this research, we use the continuous pole placement method to address the time delay problem in teleoperation. Compared to approximation based and prediction based methods, this method shows improved robustness. Simulations and experiments show a stable and well synchronized control. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
A Critical Review of the Physicochemical Impacts of Water Chemistry on Shale in Hydraulic Fracturing Systems
Hydraulic fracturing of unconventional hydrocarbon resources involves the sequential injection of a high-pressure, particle-laden fluid with varying pH’s to make commercial production viable in low permeability rocks. This process both requires and produces extraordinary volumes of water. The water used for hydraulic fracturing is typically fresh, whereas “flowback” water is typically saline with a variety of additives which complicate safe disposal. As production operations continue to expand, there is an increasing interest in treating and reusing this high-salinity produced water for further fracturing. Here in this paper we review the relevant transport and geochemical properties of shales, and critically analyze the impact of water chemistry (including produced water) on these properties. We discuss five major geochemical mechanisms that are prominently involved in the temporal and spatial evolution of fractures during the stimulation and production phase: shale softening, mineral dissolution, mineral precipitation, fines migration, and wettability alteration. A higher salinity fluid creates both benefits and complications in controlling these mechanisms. For example, higher salinity fluid inhibits clay dispersion, but simultaneously requires more additives to achieve appropriate viscosity for proppant emplacement. In total this review highlights the nuances of enhanced hydrogeochemical shale stimulation in relation to the choice of fracturing fluid chemistry.
54 ENVIRONMENTAL SCIENCES↗
Construction of MoS 2 /NiS 2 heterostructure with fast interfacial reaction kinetics for ultrafast sodium storage
Constructing heterostructure is a valid method to reinforcing sodium storage performance of transition metal chalcogenides materials. Herein, a simple, safe and controllable one step hydrothermal method is proposed to synthesize MoS 2 /NiS 2 heterostructure. Due to the difference in band gaps and work functions of MoS 2 and NiS 2 , the charges are redistributed at the MoS 2 /NiS 2 heterointerfaces, thereby accelerating the migration of electrons and Na + . The heterointerfaces provide extra active sites for storing Na + , thus increasing the sodium storage capacity of the heterostructure. Furthermore, the distinct redox potentials of NiS 2 and MoS 2 promote the structural stability of MoS 2 /NiS 2 heterostructure during the electrochemical reaction processes. Consequently, the obtained MoS 2 /NiS 2 heterostructure exhibits superior rate properties (339.4 mAh g –1 at 10 A g –1 ) and ultra-stable cycling stability (480.5 mAh g –1 after 350 cycles at 1 A g –1 ). Finally, this paper presents a valid strategy for creating heterostructure anodes with excellent sodium storage properties.
25 ENERGY STORAGE↗
Realization of thousand-second improved confinement plasma with Super I-mode in Tokamak EAST
Mastering nuclear fusion, which is an abundant, safe, and environmentally competitive energy, is a great challenge for humanity. Tokamak represents one of the most promising paths toward controlled fusion. Obtaining a high-performance, steady-state, and long-pulse plasma regime remains a critical issue. Recently, a big breakthrough in steady-state operation was made on the Experimental Advanced Superconducting Tokamak (EAST). A steady-state plasma with a world-record pulse length of 1056 s was obtained, where the density and the divertor peak heat flux were well controlled, with no core impurity accumulation, and a new high-confinement and self-organizing regime (Super I-mode = I-mode + e-ITB) was discovered and demonstrated. These achievements contribute to the integration of fusion plasma technology and physics, which is essential to operate next-step devices.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Dataset of ultralow temperature refrigeration for COVID 19 vaccine distribution solution
Abstract Most COVID-19 vaccines require temperature control for transportation and storage. Two types of vaccine have been developed by manufacturers (Pfizer and Moderna). Both vaccines are based on mRNA and lipid nanoparticles requiring low temperature storage. The Pfizer vaccine requires ultra-low temperature storage (−80 °C to −60 °C), while the Moderna vaccine requires −30 °C storage. However, the last stage of distribution is quite challenging, especially for rural or suburban areas, where local towns, pharmacy chains and hospitals may not have the infrastructure required to store the vaccine at the required temperature. In addition, there is limited data available to address ancillary challenges of the distribution framework for both transportation and storage stages, including safety concerns due to human exposure to large amounts of CO 2 from dry-ice sublimation, issues due to the pressure increase caused by dry-ice sublimation, and the potential issue caused by non-uniform cryogenic temperatures. As such, there is a need for test dataset to assist the development of a quick, effective, secure, and safe solution to mitigate the challenges faced by vaccine distribution logistics.
60 APPLIED LIFE SCIENCES↗
Passive cooling designs to improve heat resilience of homes in underserved and vulnerable communities
Disadvantaged communities face a growing threat to staying safe during heat waves, especially during coincident power outages. This study develops a methodology to evaluate the effectiveness of passive cooling measures (those that operate without power) to improve residential building heat resilience. Building performance is simulated for representative homes and on district scales in two disadvantaged communities in Fresno, California. Eleven passive measures are evaluated using four heat resilience metrics with and without grid power. Results show performance of the mitigation measures varies by building characteristics, surrounding environment, and power scenario. The two most effective measures were installing solar-control window films and adding roof insulation. For pre-1978 single-family homes, these two measures can reduce unmet degree-hours (UDH) indoors by 12% and 11% respectively without grid power, or 28% and 37% with grid power. Their respective UDH reductions at district scale typically range 8% — 20% and 4% — 12% without grid power, or 14% — 44% and 8% — 51% with grid power. Top floors have higher overheating risk than lower floors during extreme heat events with coincident power outages. Natural ventilation can help, reducing UDH by 21% — 26%. The methodology and findings from this study can help cities, communities, and utilities develop effective and targeted strategies to promote greater residential heat resilience.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Robust Restoration From Cyber-Physical Attacks in Active Distribution Grids With Grid-Edge IBRs
The inverter-based resources (IBRs) have enabled the integration of renewable energy at the grid edge with enhanced control capabilities to support the reliable operation of power grids. Different control frameworks, such as hierarchical or distributed architecture, have been proposed with the expansion of cyber networks for real-time monitoring and control. This evolution of critical infrastructure into cyber-physical systems also brings more vulnerabilities for the broadened attack surfaces, and significantly increases the possibility of physical system failures or outages caused by cyberattacks. Among tremendous efforts in the defense-in-depth approach, it remains challenging to provide prompt detection and accurate location of attack entry points or paths. Therefore, the prevailing restoration framework may struggle to fully consider the cyber-physical interdependence, successfully isolate the compromised cyber and physical components, and safely recover the systems without the potential risks leading to secondary outages. This paper is motivated to develop a cyber-physical restoration framework for distribution grids to recover from cyber attacks by harnessing grid-edge IBRs. The framework is first built on the operational guidelines of IBRs considering the compromised cyber layer. Then, an ambiguity set is established to represent the uncertainty of attack scenarios and their possibility levels. Next, a distributionally robust optimization model is developed to provide the optimal load restoration strategy across all scenarios. The effectiveness of the proposed model is demonstrated through various use cases on the modified IEEE 13-node and 123-node test systems. Finally, simulation results demonstrate the effectiveness and advancement of developed post-attack restoration strategies.
Cybersecurity↗
Time-lapse seismic data inversion for estimating reservoir parameters using deep learning
Geologic carbon sequestration involves the injection of captured carbon dioxide ([Formula: see text]) into subsurface formations for long-term storage. The movement and fate of the injected [Formula: see text] plume is of great concern to regulators because monitoring helps to identify potential leakage zones and determines the possibility of safe long-term storage. To address this concern, we design a deep-learning framework for [Formula: see text] saturation monitoring to determine the geologic controls on the storage of the injected [Formula: see text]. We use different combinations of porosities and permeabilities for a given reservoir to generate saturation and velocity models. We train the deep-learning model with a few time-lapse seismic images and their corresponding changes in saturation values for a particular [Formula: see text] injection site. The deep-learning model learns the mapping from the change in the time-lapse seismic response to the change in [Formula: see text] saturation during the training phase. We then apply the trained model to data sets comprising different time-lapse seismic image slices (corresponding to different time instances) generated using different porosity and permeability distributions that are not part of the training to estimate the [Formula: see text] saturation values along with the plume extent. Our algorithm provides a deep-learning assisted framework for the direct estimation of [Formula: see text] saturation values and plume migration in heterogeneous formations using the time-lapse seismic data. Our method improves the efficiency of time-lapse inversion by streamlining the large number of intermediate steps in the conventional time-lapse inversion workflow. This method also helps to incorporate the geologic uncertainty for a given reservoir by accounting for the statistical distribution of porosity and permeability during the training phase. Tests on different examples verify the effectiveness of our approach.
Geochemistry & Geophysics↗
Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects
This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.
Holcomb, Paul↗