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At least 775 records · Page 43

The Impact of Surficial Biochar Treatment on Acute H2S Emissions during Swine Manure Agitation before Pump-Out: Proof-of-the-Concept

Acute releases of hydrogen sulfide (H2S) are of serious concern in agriculture, especially when farmers agitate manure to empty storage pits before land application. Agitation can cause the release of dangerously high H2S concentrations, resulting in human and animal fatalities. To date, there is no proven technology to mitigate these short-term releases of toxic gas from manure. In our previous research, we have shown that biochar, a highly porous carbonaceous material, can float on manure and mitigate gaseous emissions over extended periods (days–weeks). In this research, we aim to test the hypothesis that biochar can mitigate H2S emissions over short periods (minutes–hours) during and shortly after manure agitation. The objective was to conduct proof-of-the-concept experiments simulating the treatment of agitated manure. Two biochars, highly alkaline and porous (HAP, pH 9.2) made from corn stover and red oak (RO, pH 7.5), were tested. Three scenarios (setups): Control (no biochar), 6 mm, and 12 mm thick layers of biochar were surficially-applied to the manure. Each setup experienced 3 min of manure agitation. Real-time concentrations of H2S were measured immediately before, during, and after agitation until the concentration returned to the initial state. The results were compared with those of the Control using the following three metrics: (1) the maximum (peak) flux, (2) total emission from the start of agitation until the concentration stabilized, and (3) the total emission during the 3 min of agitation. The Gompertz’s model for determination of the cumulative H2S emission kinetics was developed. Here, 12 mm HAP biochar treatment reduced the peak (1) by 42.5% (p = 0.125), reduced overall total emission (2) by 17.9% (p = 0.290), and significantly reduced the total emission during 3 min agitation (3) by 70.4%. Further, 6 mm HAP treatment reduced the peak (1) by 60.6%, and significantly reduced overall (2) and 3 min agitation’s (3) total emission by 64.4% and 66.6%, respectively. Moreover, 12 mm RO biochar treatment reduced the peak (1) by 23.6%, and significantly reduced overall (2) and 3 min total (3) emission by 39.3% and 62.4%, respectively. Finally, 6 mm RO treatment significantly reduced the peak (1) by 63%, overall total emission (2) by 84.7%, and total emission during 3 min agitation (3) by 67.4%. Biochar treatments have the potential to reduce the risk of inhalation exposure to H2S. Both 6 and 12 mm biochar treatments reduced the peak H2S concentrations below the General Industrial Peak Limit (OSHA PEL, 50 ppm). The 6 mm biochar treatments reduced the H2S concentrations below the General Industry Ceiling Limit (OSHA PEL, 20 ppm). Research scaling up to larger manure volumes and longer agitation is warranted.

Chen, Baitong (ORCID:0000000266071253)↗

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities: Preprint

Increased penetration of distributed variable re-newable generation may cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But due to the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network is needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69 node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multicoordination Control Strategy Performance in Hybrid Power Systems

This paper evaluates a state-space methodology of a multi-input multi-output (MIMO) control strategy using a 2 × 2 tightly coupled scenario applied to a physical gas turbine fuel cell hybrid power system. A centralized MIMO controller was preferred compared to a decentralized control approach because previous simulation studies showed that the coupling effect identified during the simultaneous control of the turbine speed and cathode airflow was better minimized. The MIMO controller was developed using a state-space dynamic model of the system that was derived using first-order transfer functions empirically obtained through experimental tests. The controller performance was evaluated in terms of disturbance rejection through perturbations in the gas turbine operation, and setpoint tracking maneuver through turbine speed and cathode airflow steps. The experimental results illustrate that a multicoordination control strategy was able to mitigate the coupling of each actuator to each output during the simultaneous control of the system, and improved the overall system performance during transient conditions. On the other hand, the controller showed different performance during validation in simulation environment compared to validation in the physical facility, which will require a better dynamic modeling of the system for the implementation of future multivariable control strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Learning Provably Stable Local Volt/Var Controllers for Efficient Network Operation

Here this paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution grids (DGs). Aiming to improve DG operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The first stage involves learning the manifold of optimal operating points determined by an ORPF instance. To synthesize local Volt/Var controllers, the learning task is partitioned into learning local surrogates (one per DER) of the optimal manifold with voltage input and reactive power output. Since these surrogates characterize efficient DG operating points, in the second stage, we develop local control schemes that steer the DG to these operating points. We identify the conditions on the surrogates and control parameters to ensure that the locally acting controllers collectively converge, in a global asymptotic sense, to a DG operating point agreeing with the local surrogates. We use neural networks to model the surrogates and enforce the identified conditions in the training phase. AC power flow simulations on the IEEE 37-bus network empirically bolster the theoretical stability guarantees obtained under linearized power flow assumptions. The tests further highlight the optimality improvement compared to prevalent benchmark methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Wave Energy Power Take-off Validation with a Hydraulicly Actuated Rotary Dynamometer and a Bi-Directional High-Power DC Supply

There are many organizations working towards the commercialization of wave energy converter technologies and are advancing their designs through the technology readiness levels (TRLs). A critical step before the field deployment of prototype wave energy converters is the validation of the subsystems and components that are contained in the wave energy converter through laboratory testing and performance characterization. In 2021, the National Renewable Energy Laboratory (NREL) developed and demonstrated a system for testing power takeoffs (PTO) with a low-speed, high-torque dynamometer and a grid-tied high-power DC power source and sink before field deployment. The hydraulic dynamometer allows for the simulation of PTO actuation from wave motion and is capable of a wide range of wave periods and heights which are represented as various speeds and torques from the dynamometer. The high-power bidirectional power supply allows for hardware in the loop and controller in the loop testing to be conducted on WEC power electronics. This presentation was made to describe the methods used by NREL research staff to test all components and sub-systems in the PTO of a novel wave energy converter before field deployment.

dynamometer↗

Wave Energy Power Take-Off Validation with a Hydraulicly Actuated Rotary Dynamometer and a Bidirectional High-Power DC Supply: Preprint

There are many organizations working towards the commercialization of wave energy converter technologies and are advancing their designs through the technology readiness levels (TRLs). A critical step before the field deployment of prototype wave energy converters is the validation of the subsystems and components that are contained in the wave energy converter through laboratory testing and performance characterization. In 2021, the National Renewable Energy Laboratory (NREL) developed and demonstrated a system for testing power takeoffs (PTO) with a low-speed, high-torque dynamometer and a grid-tied high-power DC power source and sink before field deployment. The hydraulic dynamometer allows for the simulation of PTO actuation from wave motion and is capable of a wide range of wave periods and heights which are represented as various speeds and torques from the dynamometer. The high-power bidirectional power supply allows for hardware in the loop and controller in the loop testing to be conducted on WEC power electronics. This presentation was made to describe the methods used by NREL research staff to test all components and sub-systems in the PTO of a novel wave energy converter before field deployment.

dynamometer↗

The Digital Engineering Vision for DOME: Facilitating Design, Deployment, and Operations [Poster]

DOME is a planned microreactor test facility at INL’s Materials and Fuels Complex. It is a complex system with several interdependent sub-systems such as the reactor (up to 20 MWth), radioactive confinement, temperature and pressure regulation system, ventilation system, etc. The engineering design process for such a system traditionally involves several documents from various sources and the system information is scattered across these documents. Digital engineering represents a paradigm shift through which systems are designed using digital models and integrated data. The digital engineering vision for DOME utilizes a model-based systems engineering (MBSE) approach. The system architecture, physical components, control logic, and verification experiments are all designed using MathWorks MATLAB and Simulink. This hierarchical model can combine data from multiple sources at various levels of abstraction. It can be used to simulate the facility’s operations and to test the system using different sets of parameters. Its capabilities can be expanded by interfacing it with high-fidelity multi-physics models, risk analysis tools, etc. The same model can evolve into a digital twin that can monitor operations and conduct predictive analysis using real-time sensor data from the facility. The eventual goal of this effort is to transform the end-to-end engineering of nuclear facilities in every phase of their lifecycle, including design, deployment, and operations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SinhaRoy_TechPresentation_2024 [Slides]

DOME is a planned microreactor test facility at INL’s Materials and Fuels Complex. It is a complex system with several interdependent sub-systems such as the reactor (up to 20 MWth), radioactive confinement, temperature and pressure regulation system, ventilation system, etc. The engineering design process for such a system traditionally involves several documents from various sources and the system information is scattered across these documents. Digital engineering represents a paradigm shift through which systems are designed using digital models and integrated data. The digital engineering vision for DOME utilizes a model-based systems engineering (MBSE) approach. The system architecture, physical components, control logic, and verification experiments are all designed using MathWorks MATLAB and Simulink. This hierarchical model can combine data from multiple sources at various levels of abstraction. It can be used to simulate the facility’s operations and to test the system using different sets of parameters. Its capabilities can be expanded by interfacing it with high-fidelity multi-physics models, risk analysis tools, etc. The same model can evolve into a digital twin that can monitor operations and conduct predictive analysis using real-time sensor data from the facility. The eventual goal of this effort is to transform the end-to-end engineering of nuclear facilities in every phase of their lifecycle, including design, deployment, and operations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development and characterization of an ice-selecting pumped counterflow virtual impactor (IS-PCVI) to study ice crystal residuals

Separation of particles that play a role in cloud activation and ice nucleation from interstitial aerosols has become necessary to further understand aerosol-cloud interactions. The pumped counterflow virtual impactor (PCVI), which uses a vacuum pump to accelerate the particles and increase their momentum, provides an accessible option for dynamic and inertial separation of cloud elements. However, the use of a traditional PCVI to extract large cloud hydrometeors is difficult mainly due to its small cut-size diameters (< 5 µm). Here, for the first time we describe a development of an ice-selecting PCVI (IS-PCVI) to separate ice in controlled mixed-phase cloud system based on the particle inertia with the cut-off diameter ≥ 10 µm. We also present its laboratory application demonstrating the use of the impactor under a wide range of temperature and humidity conditions. The computational fluid dynamics simulations were initially carried out to guide the design of the IS-PCVI. After fabrication, a series of validation laboratory experiments were performed coupled with the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) expansion cloud simulation chamber. In the AIDA chamber, test aerosol particles were exposed to the ice supersaturation conditions (i.e., RH ice > 100 %), where a mixture of droplets and ice crystals was formed during the expansion experiment. In parallel, the flow conditions of the IS-PCVI were actively controlled, such that it separated ice crystals from a mixture of ice crystals and cloud droplets, which were of diameter ≥ 10 µm. These large ice crystals were passed through the heated evaporation section to remove the water content. Afterwards, the residuals were characterized with a suite of online and offline instruments downstream of the IS-PCVI. These results were used to assess the optimized operating parameters of the device in terms of (1) the critical cut-size diameter, (2) the transmission efficiency and (3) the counterflow-to-input flow ratio. Particle losses were characterized by comparing the residual number concentration to the rejected interstitial particle number concentration. Overall results suggest that the IS-PCVI enables inertial separation of particles with a volume-equivalent particle size in the range of ~&thinsp;10–30 µm in diameter with small inadvertent intrusion (~ &thinsp;5 %) of unwanted particles.

54 ENVIRONMENTAL SCIENCES↗

Multiscale Thermal-hydraulic analysis of the MARVEL microreactor using a coupled SAM and SCM simulation. (PPTX)

This is .pptx document presenting a summary of the paper of the same name that has been submitted and accepted to NURETH-21: MARVEL is a natural-convection-cooled sodium-potassium microreactor that is anticipated to generate 85 kilowatts of thermal energy. It will operate within Idaho National Laboratory Transient Reactor Test Facility and is being developed by the DOE Microreactor Program. MARVEL will be used to test microreactor applications, evaluate systems for remote monitoring, and develop autonomous control technologies. A thermal-hydraulic computational model of this facility is a valuable tool to study important transients and calculate the safety limits of the micro-reactor design. For this purpose, the authors have chosen to use a multiscale coupled simulation: SCM for modeling the reactor core and SAM for the reactor's primary cooling system. SCM is MOOSE physics module for subchannel analysis, which was designed to model single-phase flows through liquid-metal cooled, wire-wrapped fuel pin sub-assemblies, ordered in a triangular lattice. The SCM code was modified to be able to model MARVEL?s unique geometry. SAM is a systems analysis module based on the MOOSE framework. It aims to provide fast-running, whole-plant transient analyses capability with improved-fidelity for various advanced reactor types. The coupling between the two SCM and SAM for MARVEL modeling is done implementing a domain over-lapping approach. The resulting coupled simulation can model transients such as reactor startup/shutdown and provide an intermediate fidelity picture of the temperature field and other variables, in the core. Results for the steady-state simulations are presented in the article as well as flow blockage transient.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities

Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Identification of key parameters controlling demographically structured vegetation dynamics in a Land Surface Model

This dataset includes outputs of 5000 simulations of CLM4.5(ED) to quantify the sensitivity of the model outputs to changes in model parameters using the Fourier Amplitude Sensitivity Test (FAST). Each simulation is generated by simultaneously sampling from 15% deviations of the default values of >80 vegetation parameters. This dataset includes 1) model codes of CLM4.5(ED) used for the sensitivity analysis; 2) the parameter samples; and 3) the corresponding model outputs of vegetation status (e.g., Gross Primary Production, Leaf Area Index and Biomass) and demography (e.g., diameter growth and mortality rates). The outputs are organized to the format of the FAST toolbox (https://sites.google.com/site/xuchongang/uasatoolbox).

54 ENVIRONMENTAL SCIENCES↗

End-to-end differentiable digital twin for the IOTA/FAST facility

As the design complexity of modern accelerators grows, there is more interest in using controllable-fidelity simulations that have fast execution time or can yield additional insights about accelerator state. One notable example of additional information are gradients of physical observables with respect to design parameters produced by differentiable simulations. The IOTA/FAST facility has recently begun a program to implement and experimentally validate an end-to-end digital twin to serve as a virtual accelerator test stand, allowing for rapid prototyping of new software and experiments with minimal beam time costs. In this contribution we will discuss our plans and progress. Specifically, we will cover the selection and benchmarking of both physics and ML codes for linac and ring simulation, the development of generic interfaces between surrogate and physics-based sections, and presenting the control interface as either a deterministic event loop or a fully asynchronous EPICS soft input/output controller. We will also discuss challenges in model calibration and uncertainty quantification, as well as future plans to implement larger proton accelerators like PIPII and Booster.

Kuklev, N. [Fermilab]↗

Report for 2.2.1 Task 1: Support of Operator in the Loop Studies to be Conducted in the HSSL

Idaho National Laboratory (INL) has contracted IFE to support human factors research to understand how to perform control room modernizations in a manner that maintains or improves human and overall system performance. The US Nuclear industry and in particular several utilities are currently moving forward with a Main Control Room (MCR) modernization projects or future projects to replace current analogue systems with digital. The focus of the current project was to look at different interface platforms and different ways to present information to the interface end user, the plant operator. IFE’s focus was to develop digital soft controls HSI for the Generic Pressurized Water Reactor (gPWR) and a Larger Screen Display (LSD) to support the Control Room Operators. The IFE Advanced Control Room is a combination of the digital soft controls HSI and the LSD that provides a unique opportunity for testing in the HSSL at Idaho National Laboratory.

99 GENERAL AND MISCELLANEOUS↗

Test Plan for the Boiling Water Reactor Dry Cask Simulator

The thermal performance of commercial nuclear spent fuel dry storage casks are evaluated through detailed numerical analysis . These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission (NRC). Carefully measured data sets generated from testing of full sized casks or smaller cask analogs are widely recognized as vital for validating these models. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a cask in part by increasing the efficiency of internal conduction pathways and by increasing the internal convection through greater canister helium pressure. These same vertical, canistered cask systems rely on ventilation between the canister and the overpack to convect heat away from the canister to the environment for both above and below-ground configurations. While several testing programs have been previously conducted, these earlier validation attempts did not capture the effects of elevated helium pressures or accurately portray the external convection of above-ground and below-ground canistered dry cask systems. The purpose of the investigation described in this report is to produce a data set that can be used to test the validity of the assumptions associated with the calculations presently used to determine steady-state cladding temperatures in modern vertical, canistered dry cask systems. The BWR cask simulator (BCS) has been designed in detail for both the above-ground and below-ground venting configurations. The pressure vessel representing the canister has been designed, fabricated, and pressure tested for a maximum allowable pressure (MAWP) rating of 24 bar at 400 deg C. An existing electrically heated but otherwise prototypic BWR Incoloy-clad test assembly is being deployed inside of a representative storage basket and cylindrical pressure vessel that represents the canister. The symmetric single assembly geometry with well-controlled boundary conditions simplifies interpretation of results. Various configurations of outer concentric ducting will be used to mimic conditions for above and below-ground storage configurations of vertical, dry cask systems with canisters. Radial and axial temperature profiles will be measured for a wide range of decay power and helium cask pressures. Of particular interest is the evaluation of the effect of increased helium pressure on allowable heat load and the effect of simulated wind on a simplified below ground vent configuration. While incorporating the best available information, this test plan is subject to changes due to improved understanding from modeling or from as-built deviations to designs. As-built conditions and actual procedures will be documented in the final test report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Bridging the simulator gap: Measuring motivational bias in digital nuclear power plant environments

Using digital NPP simulator facilities for research in Human Reliability Analysis (HRA) and nuclear power research is increasingly popular. For this work, we propose a method for characterizing and quantifying the gap between data collected in a simulator and data that reflect NPP operations. Using novice operators, we demonstrate how to manipulate and measure the impact of the simulator environment on operator actions. A set of biases are proposed to characterize factors introduced by the simulator environment. There are two categories of simulator bias: Environmental Biases (physical differences between the simulator and the control room), and Motivational Biases (cognitive differences between training in a simulator and operating a NPP). This study examines Motivational Bias. A preliminary causal model of Motivational Biases is introduced and tested in a demonstration experiment using 30 student operators. Data from 41 simulator sessions are analyzed. Data include crew characteristics, operator surveys, and time to recognize and diagnose the accident in the scenario. Quantitative models of the Motivational Biases using Structural Equation Modeling (SEM) are proposed. With these models, we estimate how the effects of the scenario conditions are mediated by simulator bias, and we demonstrate how to quantify the strength of these effects.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Evaluation of nonlinear control performance of air handling units under variable operation conditions using root distribution approach

The control systems at Air handling units (AHUs) have nonlinear nature, resulting potentially in sluggish, aggressive, or oscillatory responses under variable operation conditions. This paper is to develop an approach for evaluating the nonlinear control performance of AHUs under variable operation conditions and for identifying the impact of varying multiple operation parameters which guides controller design. To do so, an operation parameter-based root distribution technique, intended to sketch the paths traced by closed-loop poles as multiple operation parameters are varied, is first introduced. The technique—which may be viewed as an extension of conventional, single-variable root locus—is then applied to a fan speed control system that includes a motor with a variable frequency drive and a supply fan with an air duct under variable fan speed and duct static pressure. Using the technique, the system’s stability region is graphically identified. The system is also found to be aggressive and gradually lose its stability as the fan speed decreases and the duct static pressure increases, which is validated by the field tests. Here, the root distribution approach is an effective tool to evaluate the performance of any nonlinear control systems at AHUs with multiple variable operation parameters without requiring time-domain simulations.

42 ENGINEERING↗

Virtual Tokamak for Test and Development of Plasma Control Applied to NSTX-U

Safe and efficient operation of tokamak experiments depends on shot preparation prior to the experiment to maximize performance and avoid issues that are predictable consequences of known physics. The General Atomics TokSys toolbox is used to test and develop the plasma control system (PCS) on numerous tokamaks around the world. Tokamaks that use a version of the DIII-D PCS can connect it to a TokSys simulation and control a virtual version of the tokamak with the real PCS. Recent upgrades to the simulation include more detailed profile and transport modeling to support design and implementation of optimized scenarios. The simulation combines a module called “Profiles” that simulates the 1D profiles of density, pressure, and current and a module called “GSevolve'' that evolves the 2D Grad-Shafranov equilibrium. The “Profiles'' module primarily uses simplified models for fueling, heating, and current. The TRANSP code provides precomputed diffusion coefficients and heating/current drive profiles from radio-frequency and neutral beam sources for the scenarios being simulated. The fidelity of a simulation can be enhanced by analyzing it with TRANSP and making corrections to the precomputed values and iterating until convergence. Simulations of the National Spherical Torus Upgrade (NSTX-U) are presented. It is shown that the simulation reproduces the experimental profile evolution. Here, the simulation has also been upgraded to reproduce the experimental outcome at points of bifurcation. This is demonstrated with a simulation of vertical displacement in NSTX-U.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗