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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Data for Solvent-Free Enzymatic Esterification of Free Fatty Acids with Glycerol for Biodiesel Application: Optimized Using the Taguchi Experimental Method

Presence of free fatty acids along with glycerides poses a technical difficulty for biodiesel production. This work used a Taguchi L9 design to optimize the solvent-free enzymatic process to result in the esterification of oleic acid with glycerol. Under optimal conditions the esterification reaction temperature of 60°C, enzyme dose of 5 wt%, glycerol: oleic acid molar ratio of 5:1, and reaction time of 3 h, a 75.235 ± 2.19% conversion of oleic acid to esters was achieved. With the addition of molecular sieves, the conversion increased to 86.73% ± 1.09%. However, using the parameters predicted by Taguchi design (60°C, 5 wt%, 5:1, and 4.5 h), 88.5% ± 1.11% of oleic acid could be converted to esters derivative. Diglycerides were the major product, and the reaction equilibrium was attained after 4 h. The immobilized enzyme could be used up to seven times with only a 10% reduction in the conversion. Thus, the process can efficiently reduce the free fatty acid content of oil to make it suitable for biodiesel production.

Conversion↗
DOE OSTI2014

TH-C-17A-08: Monte Carlo Based Design of Efficient Scintillating Fiber Dosimeters

Purpose: To accurately predict Cherenkov radiation generation in scintillating fiber dosimeters. Quantifying Cherenkov radiation provides a method for optimizing fiber dimensions, orientation, optical filters, and photodiode spectral sensitivity to achieve efficient real time imaging dosimeter designs. Methods: We develop in-house Monte Carlo simulation software to model polymer scintillation fibers' fluorescence and Cherenkov emission in megavoltage clinical beams. The model computes emissions using generation probabilities, wavelength sampling, fiber photon capture, and fiber transport efficiency and incorporates the fiber's index of refraction, optical attenuation in the Cherenkov and visible spectrum and fiber dimensions. Detector component selection based on parameters such as silicon photomultiplier efficiency and optical coupling filters separates Cherenkov radiation from the dose-proportional scintillating emissions. The computation uses spectral and geometrical separation of Cherenkov radiation, however other filtering techniques can expand the model. Results: We compute Cherenkov generation per electron and fiber capture and transmission of those photons toward the detector with incident electron beam angle dependence. The model accounts for beam obliquity and nonperpendicular electron fiber impingement, which increases Cherenkov emission and trapping. The rotational angle around square fibers shows trapping efficiency variation from the normally incident minimum to a maximum at 45 degrees rotation. For rotation in the plane formed by the fiber axis and its surface normal, trapping efficiency increases with angle from the normal. The Cherenkov spectrum follows the theoretical curve from 300nm to 800nm, the wavelength range of interest defined by silicon photomultiplier and photodiode spectral efficiency. Conclusion: We are able to compute Cherenkov generation in realistic real time scintillating fiber dosimeter geometries. Design parameters incorporate fiber dimensions, orientations, several types of detector spectral response, optical coupling filters and light transport. We can vary these parameters to design and optimize high efficiency real time dosimeters capable of enhancing external beam patient safety and treatment accuracy. This research was supported in part by a GAANN Fellowship from the Department of Education.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Solvent‐free enzymatic esterification of free fatty acids with glycerol for biodiesel application: Optimized using the Taguchi experimental method

Abstract Presence of free fatty acids along with glycerides poses a technical difficulty for biodiesel production. This work used a Taguchi L9 design to optimize the solvent‐free enzymatic process to result in the esterification of oleic acid with glycerol. Under optimal conditions the esterification reaction temperature of 60°C, enzyme dose of 5 wt%, glycerol: oleic acid molar ratio of 5:1, and reaction time of 3 h, a 75.235 ± 2.19% conversion of oleic acid to esters was achieved. With the addition of molecular sieves, the conversion increased to 86.73% ± 1.09%. However, using the parameters predicted by Taguchi design (60°C, 5 wt%, 5:1, and 4.5 h), 88.5% ± 1.11% of oleic acid could be converted to esters derivative. Diglycerides were the major product, and the reaction equilibrium was attained after 4 h. The immobilized enzyme could be used up to seven times with only a 10% reduction in the conversion. Thus, the process can efficiently reduce the free fatty acid content of oil to make it suitable for biodiesel production.

09 BIOMASS FUELS↗
DOE OSTI2014

Reduction of scattering using thin all-dielectric shells designed by stochastic optimizer

Adaptive differential evolution method has been used for optimization of all-dielectric multilayer coatings in order to reduce total scattering from spherical targets. The optimal refractive index profiles have been found for various sizes of targets and thicknesses of coatings. Few profile types that appear to be optimal for various geometrical parameters have been identified. Scattering of the target with diameter of 0.75 λ has been reduced by 85% using 0.16 λ thick coating formed by isotropic dielectric materials. For larger targets, scattering reduction becomes smaller, but it still reaches 50% for targets with the diameter of 1.5 λ. The obtained designs provide a route to implement cloaking without the use of magnetic and anisotropic metamaterials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

SU-E-T-500: Initial Implementation of GPU-Based Particle Swarm Optimization for 4D IMRT Planning in Lung SBRT

Purpose 4D-IMRT planning, combined with dynamic MLC tracking delivery, utilizes the temporal dimension as an additional degree of freedom to achieve improved OAR-sparing. The computational complexity for such optimization increases exponentially with increase in dimensionality. In order to accomplish this task in a clinically-feasible time frame, we present an initial implementation of GPU-based 4D-IMRT planning based on particle swarm optimization (PSO). Methods The target and normal structures were manually contoured on ten phases of a 4DCT scan of a NSCLC patient with a 54cm3 right-lower-lobe tumor (1.5cm motion). Corresponding ten 3D-IMRT plans were created in the Eclipse treatment planning system (Ver-13.6). A vendor-provided scripting interface was used to export 3D-dose matrices corresponding to each control point (10 phases × 9 beams × 166 control points = 14,940), which served as input to PSO. The optimization task was to iteratively adjust the weights of each control point and scale the corresponding dose matrices. In order to handle the large amount of data in GPU memory, dose matrices were sparsified and placed in contiguous memory blocks with the 14,940 weight-variables. PSO was implemented on CPU (dual-Xeon, 3.1GHz) and GPU (dual-K20 Tesla, 2496 cores, 3.52Tflops, each) platforms. NiftyReg, an open-source deformable image registration package, was used to calculate the summed dose. Results The 4D-PSO plan yielded PTV coverage comparable to the clinical ITV-based plan and significantly higher OAR-sparing, as follows: lung Dmean=33%; lung V20=27%; spinal cord Dmax=26%; esophagus Dmax=42%; heart Dmax=0%; heart Dmean=47%. The GPU-PSO processing time for 14940 variables and 7 PSO-particles was 41% that of CPU-PSO (199 vs. 488 minutes). Conclusion Truly 4D-IMRT planning can yield significant OAR dose-sparing while preserving PTV coverage. The corresponding optimization problem is large-scale, non-convex and computationally rigorous. Our initial results indicate that GPU-based PSO with further software optimization can make such planning clinically feasible. This work was supported through funding from the National Institutes of Health and Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Direct and Inverse Problems of Thermomechanics Concerning the Optimization and Identification of the Thermal Stressed State of Deformed Solids

We describe the main stages of the development of investigations originated by Prof. Vihak in the fields of the theory and methods of optimal control over the thermal processes and thermal stressed state of deformed solids, theory of inverse problems of heat conduction and thermomechanics, and the mathematical methods in the mechanics of deformable solids. We indicate the existence of close relationship between the obtained theoretical results and the applied problems of thermal power engineering motivating investigations of this kind. We describe a significant contribution made by the researchers of the Pidstryhach Institute for Applied Problems in Mechanics and Mathematics of the Ukrainian National Academy of Sciences to the development of investigations in these fields. The prospects of further development of these studies are analyzed and some facts from the life and creative activity of Prof. V. М. Vihak are presented.

42 ENGINEERING↗
DOE OSTI2020

Multi-Agent Safe Policy Learning for Power Management of Networked Microgrids

This paper presents a supervised multi-agent safe policy learning (SMAS-PL) method for optimal power management of networked microgrids (MGs) in distribution systems. While unconstrained reinforcement learning (RL) algorithms are black-box decision models that could fail to satisfy grid operational constraints, our proposed method considers AC power flow equations and other operational limits. Accordingly, the training process employs the gradient information of operational constraints to ensure that the optimal control policy functions generate safe and feasible decisions. Furthermore, we have developed a distributed consensus-based optimization approach to train the agents’ policy functions while maintaining MGs’ privacy and data ownership boundaries. After training, the learned optimal policy functions can be safely used by the MGs to dispatch their local resources, without the need to solve a complex optimization problem from scratch. Lastly, numerical experiments have been devised to verify the performance of the proposed method.

, policy gradient↗
DOE OSTI2016

Calibration of coronary calcium scores determined using iterative image reconstruction (AIDR 3D) at 120, 100, and 80 kVp

Purpose: Computed tomography (CT) radiation dose reduction is frequently achieved by applying lower tube voltages and using iterative reconstruction (IR). For calcium scoring, the reference protocol at 120 kVp with filtered back projection (FBP) is still used, because kVp and IR may influence the Agatston score (AS) and volume score (VS). The authors present a two-step method to optimize dose: first, to determine the lowest feasible exposure and highest noise thresholds; second, to define a calibration method that ensures that the AS and VS are similar to the reference protocol. Methods: AS and VS were measured for an anthropomorphic thoracic phantom that includes a calcium calibration module. The phantom was scanned on a 320-row CT scanner, at tube voltages of 120 kVp using FBP, and 120, 100, and 80 kVp using adaptive iterative dose reduction (AIDR 3D) reconstruction. The minimum CTDIs were determined based on three objective quality criteria. Calibration was performed to estimate adjusted CT number thresholds for the lower kVp acquisitions. Finally, the accuracies of the total and individual insert scores at dose level close to the minimum CTDI level were investigated and compared to low (FBP{sub LD} − 120) and high (FBP{sub HD} − 120) dose reference protocols (based on ten repeated acquisitions for each group). Results: IR allows the exposure to be reduced by 69% at 120 kVp, with no significant effect on the total scores when averaged over all included dose steps and compared to FBP-120 (AS: 693 vs 699, p = 0.182; VS: 588 vs 587 mm{sup 3}, p = 0.569). Also when averaged over ten repeated scans and compared to FBP{sub HD} − 120 (AS: 709 vs 704, p = 0.435; VS: 604 vs 601 mm{sup 3}, p = 0.479), there is no statistical significant effect. Reducing the peak tube voltage allows even greater dose reductions: 73% at 100 kVp and 76% at 80 kVp. The calibrated CT number thresholds for analysis at 120, 100, and 80 kVp were, respectively, 130, 133, and 160 HU for the Agatston score, and 130, 132, and 140 HU for the volume score. Following the calibration, the mean scores of the four groups with dose variation were not significantly different from the reference protocol, at 100 kVp (AS: 698 vs 699, p = 0.818; VS: 584 vs 587 mm{sup 3}, p = 0.365) or at 80 kVp (AS: 698 vs 699, p = 0.996; VS: 586 vs 587 mm{sup 3}, p = 0.827). Similarly, there was no significant score difference with FBP{sub LD} − 120 during repeated scanning: 100 kVp (AS: 690 vs 694, p = 0.394; VS: 579 vs 585 mm{sup 3}, p = 0.168) and 80 kVp (AS: 703 vs 694, p = 0.115; VS: 588 vs 585 mm{sup 3}, p = 0.613). Compared to FBP{sub HD} − 120 group, the relative score deviation for the accuracy of the 400 and 800 mg/cm{sup 3} HA inserts with 3 and 5 mm diameter is less than 7%. However, the relative deviation of the smaller 1 mm inserts is poorer (up to 41% deviations for scores <3). Conclusions: With iterative reconstruction using AIDR 3D, deviations of the total Agatston and volume scores remain within 4% of the reference protocol. The 1 mm inserts were detected as calcification, but scores less than ten tend to be underestimated. Following the calibration process, the application of IR in combination with reduced tube voltages allows up to 76% lower radiation dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Interplay between Approximation Theory and Renormalization Group

The review presents general methods for treating complicated problems that cannot be solved exactly and whose solution encounters two major difficulties. First, there are no small parameters allowing for the safe use of perturbation theory in powers of these parameters, and even when small parameters exist, the related perturbative series are strongly divergent. Second, such perturbative series in powers of these parameters are rather short, so that the standard resummation techniques either yield bad approximations or are not applicable at all. The emphasis in the review is on the methods advanced and developed by the author. One of the general methods is Optimized Perturbation Theory now widely employed in various branches of physics, chemistry, and applied mathematics. The other powerful method is Self-Similar Approximation Theory allowing for quite simple and accurate summation of divergent series. These theories share many common features with the method of renormalization group, which is briefly sketched in order to stress the similarities in their ideas and their mutual interconnection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Optimal Control for Fast Frequency Response and Black-Start using Embedded Storages with Grid-Forming Control

The grid-forming inverter is regarded as the solution for integrating high levels of renewable resources into future power systems. Ensuring the stable operation of grids necessitates that grid-forming inverters offer fast frequency response. This report introduces an optimal control method that coordinates the embedded storage within the grid-forming control model with conventional synchronous generators. The optimized active power reference for the embedded storage is generated using receding horizon optimization control, aiming to keep the center of inertia frequency within acceptable limits. The effectiveness of the proposed control is verified through testing in the IEEE 39-bus system. In addition, with grid-forming capability, we will also investigate the application of using mobile embedded storages as black-start units to provide cranking power to energize non-blackstart generators in a black-start process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

The Global Optimization of Pt{sub 13} Cluster Using the First-Principle Molecular Dynamics with the Quenching Technique

The high-temperature first-principle molecular dynamics method used to obtain the low energy configurations of clusters [L. L. Wang and D. D. Johnson, PRB 75, 235405 (2007)] is extended to a considerably large temperature range by combination with the quenching technique. Our results show that there are strong correlations between the possibilities for obtaining the ground-state structure and the temperatures. Larger possibilities can be obtained at relatively low temperatures (as corresponds to the pre-melting temperature range). Details of the structural correlation with the temperature are investigated by taking the Pt{sub 13} cluster as an example, which suggests a quite efficient method to obtain the lowest-energy geometries of metal clusters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Models for predicting objective function weights in prostate cancer IMRT

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR weight prediction methodologies perform comparably to the LR model and can produce clinical quality treatment plans by simultaneously predicting multiple weights that capture trade-offs associated with sparing multiple OARs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Optimizing Storage Operation for a Probabilistic Locational Marginal Pricing Forecast: Preprint

This paper explores the applicability of using dynamic programing (DP) and approximate dynamic programming (ADP) based methods for optimal dispatch of utility scale energy storage systems (ESS). In this study, the effectiveness of these approaches have been tested using the IEEE 13 node test feeder with distributed photovoltaics (PVs) and a utility scale storage system. In this work, a co-simulation based approach has been used to setup the experiment to be able to implement detailed ESS and network models. The results obtained from DP/ADP runs have been compared with three other control strategies both myopic and intelligent. Simulations results show that DP/ADP algorithms are a good candidate for optimal EES dispatch in terms of both solution quality and execution time.

25 ENERGY STORAGE↗
DOE OSTI2018

Objective PDF-Shaping-Based Economic Dispatch for Power Systems with Intermittent Generation Sources via Simultaneous Mean and Variance Minimization

With the ever increased penetration of renewables in power grid, economic power dispatch faces a challenge in terms of min-imizing the generation cost which is increasingly affected by random factors and constraints subjected to random inputs. In this context, the cost functions are random for which the widely used mean value based minimization can only achieve limited profit gain. Indeed, as the probability density function (PDF) is a comprehensive measure of characteristics of any random varia-bles, the desired optimization should address the shaping of the PDF of the generation cost function rather just its mean value. Through a simple case study, this paper firstly reveals the long tail PDF shape of the cost function when the traditional mean-value based optimization is used. This is then followed by the de-velopment of a novel PDF-shaping-based method that optimizes both the mean and variance of the PDF of the cost function. It has been shown that the proposed approach can reshape the PDF of the generation cost function so as to make it as left and as narrow as possible, leading to a significant low risk for high generation cost. Simulation tests have been included to show the effectiveness of the proposed approach and encouraging results have been obtained.

intermittent generation sources, uncertainties, PD↗
DOE OSTI2016

Development and applications of Krotov method of global control improvement

This is a survey of works on main properties, application and development of the Krotov method of global control improvement very popular among researchers of modern problems in quantum physics and quantum chemistry, applying actively optimal control methods. The survey includes a brief description of the method in comparison with well known gradient method demonstrating such its serious advantage as absence of tuning parameters; investigations aimed to make its special version for the quantum system well defined and more effective; and generalization for wide classes of control systems, including the systems of heterogeneous structure.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Embedded pairs for optimal explicit strong stability preserving Runge–Kutta methods

We construct a family of embedded pairs for optimal explicit strong stability preserving Runge–Kutta methods of order 2 ≤ p ≤ 4 to be used to obtain numerical solution of spatially discretized hyperbolic PDEs. In this construction, the goals include non-defective property, large stability region, and small error values as defined in Dekker and Verwer (1984) and Kennedy et al. (2000). The new family of embedded pairs offer the ability for strong stability preserving (SSP) methods to adapt by varying the step-size. Through several numerical experiments, we assess the overall effectiveness in terms of work versus precision while also taking into consideration accuracy and stability.

97 MATHEMATICS AND COMPUTING↗