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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Evaluating the limitations of Bayesian metabolic control analysis

Bayesian Metabolic Control Analysis (BMCA) is a promising framework for inferring metabolic control coefficients in data-limited scenarios, combining Bayesian inference with linear-logarithmic (lin-log) rate laws. These metabolic control coefficients quantify how changes in enzyme activities affect steady-state fluxes and metabolite concentrations across a metabolic network. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCC), and concentration control coefficients (CCC) under varying data availability conditions using three synthetic metabolic network models. We demonstrate that BMCA predictions are highly dependent on the inclusion of flux and enzyme concentration data, with the omission of these datasets leading to severe inaccuracies. In our synthetic, enzyme-perturbation datasets, external metabolite concentrations had minimal impact and, in some cases, their exclusion improved predictions; when external-nutrient perturbations were introduced and those concentrations were observed, gains were at most modest. Additionally, we find that posterior estimation with both ADVI and HMC can underestimate large-magnitude elasticities in our synthetic settings, with ADVI showing somewhat higher variance under strong up-regulation; thus, recovering |elasticity| ≳ 1.5 remains challenging regardless of the inference engine. ADVI also fails to accurately infer allosteric interactions, even when regulatory effects are strong. While BMCA maintains reasonable accuracy in partially recovering the rankings of the highest FCC values, its estimates of absolute values remain constrained by prior assumptions and data limitations. Our findings reveal the BMCA algorithm’s strengths and weaknesses, providing guidance on its application in metabolic engineering, and highlighting the need for methodological refinements to enhance its predictive capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A data-driven approach to real-time vertical position estimation for NSTX-U vertical stability control

In this paper, a database of 77 996 plasma equilibrium reconstructions from 727 discharges during the initial operation of the NSTX-U spherical tokamak is analyzed to develop a statistically robust model of the plasma vertical position for real-time control. A variety of regression models are developed and tested, ranging in complexity from linear models to deep neural networks, and including input signals ranging from the four pairs of flux loops used historically on NSTX-U up to the full set of 389 real-time signals available to the plasma control system. A linear model based on 140 real-time magnetics signals is found to offer excellent accuracy, with a coefficient of determination R 2 = 0.906. The robustness of this model to limited training data, new operating scenarios, and signal errors is tested, and a procedure is demonstrated to tune the model parameters to optimize its robustness. A time-dependent plasma equilibrium solver, TokaMaker, is used to simulate vertical stability control in NSTX-U, demonstrating that it should be possible to iteratively tune the parameters of a linear vertical position model to stabilize both positive and negative triangularity plasmas in future experiments.

magnetic diagnostics↗
DOE OSTI2024

An innovative SR-WEC for a market-disruptive LCOE

The objective of DE-EE0008630: An innovative SR-WEC for a market-disruptive LCOE was to develop and test a scaled prototype of the Surface-Riding Wave Energy Converter that can result in a market-disruptive Levelized Cost of Energy by a combination of an extended operating window, substantially lowered cost and amplified average power output by simple optimum control. Initially conceptualized as a floating linear electrical generator (LEG), the SR-WEC evolved into an intermediate-scale version where multiple LEGs were mounted on a floating cylindrical body, driven by the need to enhance scalability and improve power performance.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Solid State Transformer Controls for Mitigation of E3a High-Altitude Electromagnetic Pulse Insults

This paper explores the use of a solid state transformer (SST) to mitigate the 𝐸 3𝐴 component of a high-altitude electromagnetic pulse (HEMP) insult using external energy storage optimal control techniques. In lieu of conventional passive blocking devices or feedback-controlled energy storage devices, a novel implementation of Hamiltonian error tracking is utilized to develop a feedback control law for the variable converter ratio in an SST. The findings of the simulations performed in this paper suggest that additional energy storage is not necessary to protect an individual load from a HEMP insult. The simulations performed examine the response of a single-phase SST connected to a single voltage source on a long transmission line on the one side and a single linear resistor on the other. The control law is specifically developed for the late-time, low-frequency portion of a HEMP insult, namely the 𝐸 3𝐴 components. The Hamiltonian error-based converter ratio control law is compared with nonlinear optimal feedforward controls to show that the HSSPFC is an external energy storage optimal controller.

HEMP mitigation↗
DOE OSTI2024

Optimal Control of SOEC-Based Hydrogen Production Systems for Demand Response Using Deep Reinforcement Learning in Smart Grids

Solid oxide electrolysis cell (SOEC) hydrogen production technology can range in size from small, appliance-size equipment to large-scale, central production facilities that can be tied directly to renewable or non-greenhouse-gas-emitting forms of electricity production, making it an ideal resource for demand response (DR). The SOEC hydrogen production system is a complex integrated system that encompasses fluid dynamics, electrical dynamics, and electrochemical and thermal dynamics, all of which involve non-linearity and non-convexity. Proper control of the SOEC hydrogen production system is crucial to enable its participation in the DR program. Here, to overcome the difficulty of designing an explicit control law for such nonlinear systems with nonconvex optimization features in DR applications, deep reinforcement learning (DRL) is explored to achieve the optimal control of the SOEC system for DR participation. Specifically, a twin delayed deterministic policy gradient (TD3) control framework is applied to achieve optimal response performance during DR events by considering power tracking error and hydrogen production efficiency with a suitable reward function. Two case studies with grid connections for tracking different DR commands were investigated. The first case study involved operating conditions reaching the boundaries, while the second involved operating conditions within the boundaries. The results showed that the proposed DRL-based control for SOEC can track the DR signal in a timely manner while maintaining high energy efficiency.

08 HYDROGEN↗
DOE OSTI2025

Universal control in bosonic systems with weak Kerr nonlinearities

Resonators with weak single-photon self-Kerr nonlinearities can theoretically be used to prepare Fock states in the presence of a loss much larger than their nonlinearities. Two necessary ingredients are large displacements and a two-photon (parametric) drive. Here, in this study, we find that these systems can be controlled to achieve any desired gate operation in a finite-dimensional subspace (whose dimensionality can be chosen at will). Moreover, we show that the two-photon driving requirement can be relaxed and that full controllability is achievable with only one-photon (linear) drives. We make use of both Trotter-Suzuki decompositions and gradient-based optimization to find control pulses for a desired gate, which reduces the computational overhead by using a small blockaded subspace. We also discuss the infidelity arising from input power limitations in realistic settings, as well as from corrections to the rotating-wave approximation. Our universal control protocol opens the possibility for quantum information processing using a wide range of lossy systems with weak nonlinearities.

Yuan, Ming [Univ. of Chicago, IL (United States)] ↗
DOE OSTI2024

Robust PID Control Against Nonlinear Uncertainties in Modern Power Systems with Microgrids

This paper investigates the problem of robust PID control for nonlinear power systems with uncertainties. In this paper, we analyze the challenges posed by nonlinearities and uncertainties in power systems, as well as the limitations of traditional linearization methods. On this basis, a PID control design method is proposed, which utilizes only the Lipschitz constant information of the nonlinear uncertainties to achieve global stability control for the power systems. The paper provides a rigorous mathematical foundation to demonstrate the effectiveness and robustness of the controller. Finally, simulation studies are conducted to validate and evaluate the performance of the proposed model, algorithm, and controller design.

Yuan, Shuo↗
DOE OSTI2024

Multi-Fidelity Modeling and Control for Building Temperature Control

The ability to control energy loads such as a building's heating, ventilation, and air conditioning (HVAC) system can help facilitate increased penetration of variable renewable energy sources into the electric grid. To be able to control these HVAC systems more effectively, detailed simulations of the corresponding building physics is becoming increasingly important. These detailed simulations can be complex, nonlinear, and can require immense computational power when used in an advanced control method such as model predictive control (MPC), prompting the need to explore less computationally intensive strategies. In this work, a multi-fidelity approach is proposed to combine samples from a complex, high-fidelity model with a simple, low-fidelity model within the MPC control loop. More specifically, the parameters of a reduced-order, linear building model are periodically updated with knowledge from its high-fidelity counterpart - an EnergyPlus model - in an online fashion using a Gaussian Process surrogate model. Hence, highly accurate predictions of current and future conditions in a building are maintained with a substantially reduced computational burden compared to using the high-fidelity models alone. In other words, this linear parameter varying model preserves the low computational requirements of a low-order linear model while accurately modeling a building's dynamics. This allows a building controller to take highly informed actions without requiring a large computational budget.

building modeling↗
DOE OSTI2024

Large radial shift experiments in RHIC and their implications for EIC design

The Hadron Storage Ring (HSR) in the future Electron-Ion Collider (EIC) must operate over a broad range of design circumferences. In 2018 preliminary beam studies on the circumference adjustment capabilities of the Relativistic Heavy Ion Collider (RHIC) were performed by applying a small momentum offset to the circulating bunches without adjusting any bending magnets. The off-momentum linear optics were corrected back to on-momentum conditions. Applying a similarly small deviation to the dipole fields of a select set of bending magnets provides a large radial shift over much of the RHIC (or HSR) circumference while leaving the design trajectory unchanged in the insertion regions. Here, this paper presents the design of the different lattice configurations foreseen as the most viable options for the required HSR circumference changes, and highlights the modifications necessary for regular operations and to allow for testing these new settings in RHIC. Experimental results from 2021 and 2022 are reviewed and compared to model predictions obtained from both MAD-X and Bmad. The implications of these results for HSR design are discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Adaptive Power Flow Approximations With Second-Order Sensitivity Insights

The power flow equations are fundamental to power system planning, analysis, and control. However, the inherent non-linearity and non-convexity of these equations present formidable obstacles in problem-solving processes. To mitigate these challenges, recent research has proposed adaptive power flow linearizations that aim to achieve accuracy over wide operating ranges. The accuracy of these approximations inherently depends on the curvature of the power flow equations within these ranges, which necessitates considering second-order sensitivities. In this paper, we leverage second-order sensitivities to both analyze and improve power flow approximations. We evaluate the curvature across broad operational ranges and subsequently utilize this information to inform the computation of various sample-based power flow approximation techniques. Additionally, we leverage second-order sensitivities to guide the development of rational approximations that yield linear constraints in optimization problems. In conclusion, this approach is extended to enhance accuracy beyond the limitations of linear functions across varied operational scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Xylanolytic metabolism is regulated by coordination of transcription factors XynR and XylR in extremely thermophilic Caldicellulosiruptorales

ABSTRACT Global transcription factors (TFs) control metabolic processes in bacteria to efficiently utilize available carbon. The orderCaldicellulosiruptoraleshas drawn interest due to the ability of its members to degrade components of lignocellulosic biomass. Regulatory reconstruction ofAnaerocellum (f. Caldicellulosiruptor) besciiidentified two major global transcription factors for xylan utilization, XynR and XylR, and the corresponding putative transcription factor binding sites. Recombinant versions of XynR (LacI family) and XylR (ROK family) were subjected to fluorescence polarization (FP) and biolayer interferometry (BLI) analysis to confirm the predicted binding sites. Four XynR sites and two XylR sites were validated, accounting for 20 of 26 genes regulated by XynR and six of seven genes regulated by XylR. Bioinformatic analysis of the individual genes controlled by the two regulators showed an inter-dependent scheme for xylan conversion; the transport of xylooligosaccharides (XOS) is dependent on XylR, while enzymes responsible for hydrolysis are controlled by both regulators. For xylose catabolism by the xylose isomerase-xylulose kinase pathway, regulation is also split, with XylR controlling xylose isomerase and XynR controlling xylokinase. The XynR/XylR regulator pair withinA. besciiis conserved in all sequenced species ofCaldicellulosiruptorales, suggesting similarities in regulating linear xylan conversion. In other xylanolytic thermophiles, XylR homologs control xylan degradation, compared to just 6 out of 26 genes forA. bescii. These results show that two separate regulatory schemes (dual repression) are coordinated byA. besciito effectively regulate the hemicellulose inventory and xylan catabolism. IMPORTANCE To take full advantage of extreme thermophiles as platform metabolic engineering microorganisms, the tools for genetic manipulation must be further developed, and strategies that exploit a better understanding of metabolic regulation need to be discerned.Anaerocellum bescii, the most studied of the extremely thermophilic fermentative anaerobic bacteria that can utilize microcrystalline cellulose, can degrade microcrystalline cellulose and hemicellulose and has been metabolically engineered to convert the resulting sugars to products such as ethanol and acetone. For xylan, in particular, two major global transcription factors (TFs), XynR and XylR, play a role in sugar metabolism, although their predicted regulatory interdependence from bioinformatics analysis has not been elucidated experimentally. Here, fluorescence polarization (FP) and biolayer interferometry (BLI) were used to explore this issue to support metabolic engineering efforts aimed at improving carbohydrate processing to industrial chemicals.

Biotechnology & Applied Microbiology↗
DOE OSTI2025

Resilient State Recovery Using Prior Measurement Support Information

Resilient state recovery of cyber-physical systems has attracted much research attention due to the unique challenges posed by the tight coupling between communication, computation, and the underlying physics of such systems. By modeling attacks as additive adversary signals to a sparse subset of measurements, this resilient recovery problem can be formulated as an error correction problem. To achieve exact state recovery, most existing results require less than 50% of the measurement nodes to be compromised, which limits the resiliency of the estimators. In this paper, we show that observer resiliency can be further improved by incorporating data-driven prior information. Here, we provide an analytical bridge between the precision of prior information and the resiliency of the estimator. By quantifying the relationship between the estimation error of the weighted ℓ 1 observer and the precision of the support prior, this quantified relationship provides guidance for the estimator’s weight design to achieve optimal resiliency. Several numerical simulations and an application case study are presented to validate the theoretical claims.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

ANS Winter 2024 Summary: Optimizing the ATF-2Ramp Power Profile

When the Halden Boiling Water Reactor closed down in 2018, a need to restore the capability for in-reactor power ramp testing arose. Such testing is valuable for studying pellet-clad interaction phenomena in nuclear fuels. The data from these studies is of great interest to a number of research programs, including the accident-tolerant fuel (ATF) program at Idaho National Laboratory (INL). In 2022, Woolstenhulme et al. proposed several power ramp testing ideas using facilities at INL, including irradiation in the Transient Reactor Test Facility (better known as TREAT) and the Advanced Test Reactor (ATR) [1]. Worrall et al. [2] and Labossiere-Hickman et al. [3] subsequently performed feasibility studies for the ATR testing options in 2023. This summary further investigates the three-pin trefoil design (Fig. 1) for the proposed ATF-2Ramp Experiment discussed in Labossiere-Hickman et al. [3]. ATF-2Ramp is designed to operate in the center flux trap (CFT) of the ATR during a powered axial locator mechanism (PALM) cycle: a short, variable-powered cycle with an asymmetric power distribution. Previously, it was shown that tailoring the thickness of the hafnium (Hf) neutron shields (“mini-shrouds”) surrounding each pin offered a degree of control sufficient to achieve the programmatic linear heat generation rate (LHGR) targets for ATF-2Ramp during the high-power period of a PALM cycle. New work involves shortening the experiment test train for consistency with the fuel pins in ATF-2D [4] and then shaping the axial power profile of the three test pins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Reinforcement Learning Control for Enhancing Marine Hydrokinetic Turbine Energy Generation

This paper proposes a reinforcement learning-based method to maximize power generation for a direct-drive marine hydrokinetic turbine. A high levelized cost of energy (LCOE) is preventative in the widespread adoption of many marine energy conversion technologies. A straightforward way to reduce LCOE is to increase conversion efficiency and ensure maximum energy generation. The proposed method utilizes a damping control methodology, varying applied generator torque via a linear relationship between the applied damping coefficient and rotor speed. A state-action-reward-state-action (SARSA) algorithm has been used to learn the optimal control action for a given flow velocity. The proposed SARSA methodology uses Gaussian radial basis functions to create a three-dimensional surface to estimate the relationship between damping coefficient, incoming flow velocity, and coefficient of power (C p ). Here, the SARSA algorithm was compared against a baseline optimal tip speed ratio controller over a year-long flow velocity case profile while considering the effects of biofouling on the turbine system, where the proposed RL method generated 0.92% more energy than the baseline.

Damp↗
DOE OSTI2026

Demonstration of tokamak vertical stability control based on non-inductive Faraday-effect polarimetry measurements

Long-pulse or steady-state fusion reactors are envisioned to control vertical stability based on non-inductive measurements, i.e. that do not rely on temporal change of magnetic field. For the first time, vertical stability control using non-inductive Faraday-effect polarimetry measurements has been demonstrated. The Radial Interferometer-Polarimeter system on DIII-D is capable of microsecond resolution and was used to absolutely determine the vertical position of the plasma magnetic axis Z 0 . A vertical stability controller was developed to robustly stabilize diverted plasmas using Faraday-based measurements. The system was able to stabilize against vertical displacement events with growth rates up to 350 s -1 in elongated and elliptical plasma shapes, and instabilities with even higher growth rates are likely to be controllable with further improvements to controller tuning. Tests show that the Faraday-based controller remains effective and is capable of recovering from loss of control even when the plasma vertical position is far from the region where the linear model used to calculate Z 0 is most valid. Faraday control has also been activated during plasma ramp-up, demonstrating the robustness of the technique to larger systematic diagnostic uncertainty at low electron density.

Faraday-effect polarimetry↗
DOE OSTI2026

Experimental longitudinal emittance manipulation using laser-based photoionization in the Fermilab Linac

A series of simulations and beam studies were conducted at Fermilab’s linear accelerator to evaluate the effectiveness of longitudinal emittance control via laser-induced photoionization. While similar laser techniques have been employed at Fermilab to enhance injection and extraction efficiency into the Booster, the work presented here focuses on extending these methods to bunch-by-bunch manipulation. This approach utilizes fine-scale correction of the H- bunches’ longitudinal spatial distribution. In theory, loosely confined particles in longitudinal phase space contribute to emittance growth during acceleration. By selectively removing these outlying particles through laser scraping (H- + γ → H + e-), this growth can be reduced. This report presents experimental results from both symmetric and asymmetric longitudinal scraping of H⁻ bunches in the Fermilab linac, which were subsequently injected into Booster, and evaluates the broader applicability of this method for future high-intensity accelerator operations.

Landon, Parker [Boston U.; Fermilab]↗
DOE OSTI2025

Fully Homomorphic Encryption

This code implements a Fully Homomorphic Encryption (FHE) system, enabling secure computation on encrypted data without requiring decryption. It supports encryption, decryption, and homomorphic operations like matrix multiplication and addition. This code is adaptable for integrating FHE into linear-time invariant (LTI) systems, including digital control and filtering. With proper configuration from subject matter expertise, encrypted system parameters and signals can be manipulated to perform tasks like state updates, output calculations, and convolution in the encrypted domain. By preserving the structure of LTI systems while ensuring privacy, the framework facilitates secure applications in areas such as autonomous systems, signal processing, and industrial automation. The code initializes the encryption system using parameters provided in the env dictionary. These parameters include the ciphertext modulus, key dimension, plaintext fixed-point scaling factor, and noise bound. During initialization, a secret key is generated, which is essential for encrypting and decrypting data securely. The modular design allows users to tailor these parameters to specific use cases or security requirements. The code implements multiple cryptographic schemes. The learning with errors (LWE) encryption method encodes cleartext message to their plaintext fixed-point representation then encrypted into ciphertext space with additive noise. This noise ensures the security of the scheme, relying on the computational hardness of the LWE problem. The code also includes the Gentry-Sahai-Waters (GSW) scheme based off the LWE problem. Homomorphic matrix multiplication is performed between the LWE and GSW to encrypted data. This is achieved using a decomposition function on the LWE ciphertext during the multiplication operation. For higher-dimensional data, the code includes a method to encrypt entire matrices (GSWMat) using GSW encryption. These encrypted matrices can then be used for homomorphic matrix multiplications (MatMult). The decryption function uses the secret key to recover the original plaintext, removing the added noise and scaling that was originally applied during encryption.

Lois, Roberts [Idaho National Laboratory (INL), Id↗
DOE OSTI2024

Best Practices for Measuring the Modulation Transfer Function of Video Endoscopes

Endoscopes are crucial for assisting in surgery and disease diagnosis, including the early detection of cancer. The effective use of endoscopes relies on their optical performance, which can be characterized with a series of metrics such as resolution, vital for revealing anatomical details. The modulation transfer function (MTF) is a key metric for evaluating endoscope resolution. However, the 2020 version of the ISO 8600-5 standard, while introducing an endoscope MTF measurement method, lacks empirical validation and excludes opto-electronic video endoscopes, the largest family of endoscopes. Measuring the MTF of video endoscopes requires tailored standards that address their unique characteristics. This paper aims to expand the scope of ISO 8600-5:2020 to include video endoscopes, by optimizing the MTF test method and addressing parameters affecting measurement accuracy. We studied the effects of intensity and uniformity of image luminance, chart modulation compensation, linearity of image digital values, auto gain control, image enhancement, image compression and the region of interest dimensions on images of slanted-edge test charts, and thus the MTF based on these images. By analyzing these effects, we provided recommendations for setting and controlling these factors to obtain accurate MTF curves. Our goal is to enhance the standard’s relevance and effectiveness for measuring the MTF of a broader range of endoscopic devices, with potential applications in the MTF measurement of other digital imaging devices.

47 OTHER INSTRUMENTATION↗