Some problems and some recent results in stochastic control.
Stochastic optimal control applications in dynamic programming for linear and nonlinear systems
DYNAMIC PROGRAMMING↗
SEARCH · Engineering Papers
Results for “process optimization and control”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Time-optimal control of a bounded phase- coordinate process. II - High-order systems with multiple control inputs.
Time optimal control of bounded phase coordinate problem associated with large booster autopilot design, noting oscillatory system with two control inputs
Harvey, C. A.↗
Balancing Doses of EL222 and Light Improves Optogenetic Induction of Protein Production in Komagataella phaffii
ABSTRACT Komagataella phaffii, also known asPichia pastoris, is a powerful host for recombinant protein production, in part due to its exceptionally strong and tightly controlled P AOX1 promoter. MostK. phaffiibioprocesses for recombinant protein production rely on P AOX1 to achieve dynamic control in two‐phase processes. Cells are first grown under conditions that repress P AOX1 (growth phase), followed by methanol‐induced recombinant protein expression (production phase). In this study, we propose a methanol‐free approach for dynamic metabolic control inK. phaffiiusing optogenetics, which can help enhance input tunability and flexibility in process optimization and control. The light‐responsive transcription factor EL222 fromErythrobacter litoralisis used to regulate protein production from the P C120 promoter inK. phaffiiwith blue light. We used two system designs to explore the advantages and disadvantages of coupling or decoupling EL222 integration with that of the gene of interest. We investigate the relationship between EL222 gene copy number and light dosage to improve production efficiency for intracellular and secreted proteins. Experiments in lab‐scale bioreactors demonstrate the feasibility of the outlined optogenetic systems as potential alternatives to conventional methanol‐inducible bioprocesses usingK. phaffii.
Biotechnology & Applied Microbiology↗
On the stochastic maximum principle with ''average'' constraints.
Stochastic maximum principle with averaged constraint developed for control problems affected by stochastic process
RANDOM PROCESS↗
Sustainability in Directed Energy Deposition
Directed energy deposition (DED) additive manufacturing (AM) has been recognized as an efficient and sustainable technology in the field of advanced manufacturing. In the past few years, Considerable discussion has been made by researchers to promote DED AM for better performance in manufacturing. The discussions focus on basic theoretical research, process optimization and control, technology innovation, and industrial applications. However, this technology׳s environmental and economic benefits over traditional manufacturing processes are still to be seen and its sustainability is also a mystery. Here, this chapter presents a critical overview of the environmental sustainability of DED to provide a comprehensive understanding of the effects of materials, processing conditions, and geometric complexities on the energy consumption and environmental impacts of DED and provide a better guide for decision-makers in terms of selecting suitable manufacturing processes. In addition, this chapter proposes a novel framework for DED AM sustainability assessment and improvement based on the Life Cycle Assessment (LCA) method and multi-objective optimization. At last, future perspectives and recommendations for the sustainability of DED AM are put forward.
54 ENVIRONMENTAL SCIENCES↗
Precipitation hardening of laser powder bed fusion Ti-6Al-4V
Here, the laser powder bed fusion (PBF-L) additive manufacturing (AM) community has dedicated significant efforts into process optimization and control for defect-free Ti-6Al-4V. As defects become less of an issue for PBF-L Ti-6Al-4V, the processing-structure-properties (PSP) relationships between AM microstructures can now be explored to optimize mechanical properties. Lower temperature aging treatments around 550 °C in wrought Ti-6A-4V have been historically understood to precipitation harden the α phase with an ordered, hexagonal close packed (HCP) α 2 phase. The α 2 phase existed as nanoscale Ti 3 Al precipitates coherent with the parent α phase. The goal of the present investigation was to implement a vacuum heat treatment of 545 °C for 100 hours on PBF-L Ti-6Al-4V. This vacuum heat treatment took place after an initial hot isostatic pressure (HIP) treatment that decomposed the as-built, martensitic microstructure. The vacuum aging successfully produced nanoscale precipitates of α 2 phase within α-laths, confirmed via atom probe tomography (APT). Microstructural-length scale and quasi-static mechanical properties were investigated by nanoindentation and uniaxial tensile tests of miniaturized test specimens. Given the sensitivity of Ti-6Al-4V mechanical properties to small changes in chemistry, all test specimens originated from the same build. The α 2 precipitation resulted in significantly harder α-laths (≈ 2 GPa) as measured via nanoindentation, as well as a relative yield and ultimate tensile strength increase of 60 MPa and 38 MPa, respectively. Analysis of Variance (ANOVA) of the datasets revealed no statistical differences in total elongation between the HIPed and HIPed + aged specimens, indicative of the aging treatment producing a net benefit of strength with no loss in ductility.
36 MATERIALS SCIENCE↗
Integrated controls-structures optimization of a large space structure
A technique for the simultaneous optimization of structural and control elements of a large space structure is developed and demonstrated for a test problem, the NASA COFS-I Mast Flight System. General-purpose control and structural-analysis codes are applied directly to a large detailed model, with realistic objective and constraint functions. The steps in the process (structural optimization, control optimization, and system coordination) are described and illustrated with diagrams; the numerical implementation (using different computers for different steps) is discussed; and results showing significant design improvements in three COFS-I configurations are presented in graphs. When the weights of both structure and power-generating equipment are taken into account, a 40-bay truss design is found to be better than designs with 42 or 44 bays.
Padula, Sharon L.↗
Tuning the zeolite acidity enables selectivity control by suppressing ketene formation in lignin catalytic pyrolysis
Unveiling catalytic mechanisms at a molecular level aids rational catalyst design and selectivity control for process optimization. In this study, we find that the Brønsted acid site density of the zeolite catalyst efficiently controls the guaiacol catalytic pyrolysis mechanism. Guaiacol demethylation to catechol initiates the reaction, as evidenced by the detected methyl radicals. The mechanism branches to form either fulvenone (c-C 5 H 4 = C = O), a reactive ketene intermediate, by catechol dehydration, or phenol by acid-catalyzed dehydroxylation. At high Brønsted acid site density, fulvenone formation is inhibited due to surface coordination configuration of its precursor, catechol. By quantifying reactive intermediates and products utilizing operando photoelectron photoion coincidence spectroscopy, we find evidence that ketene suppression is responsible for the fivefold phenol selectivity increase. Complementary fulvenone reaction pathway calculations, along with 29 Si NMR-MAS spectroscopy results corroborate the mechanism. The proposed, flexible operando approach is applicable to a broad variety of heterogeneous catalytic reactions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Catalysts by pyrolysis: Direct observation of chemical and morphological transformations leading to transition metal-nitrogen-carbon materials
Transition metal-nitrogen-carbon materials (M-N-C catalysts) are promising electrocatalysts in polymer electrolyte fuel cells (PEFCs) and electrolyzer applications. High temperature treatment in inert atmosphere (pyrolysis) is the essential, most common method for the synthesis of M-N-C catalysts and critical to achieve high electrocatalytic activity and electronic conductivity. To this day, despite many uses and successful implementations in materials manufacturing, pyrolysis has been an entirely empirical technology, with process control and optimization relying exclusively on “Edisonian” approach. The knowledge gap in the mechanism about how the precursor is being transformed into catalysts hinders further development of the M-N-C catalysts regardless of the precursor class and processing protocols. In this work, we probed the morphological evolution and chemical transformation of a nitrogen-containing charge transfer organic salt, mixed with transition metal (iron) salt and amorphous silica powder (precursor) during the pyrolysis process via a combination of in situ synchrotron and laboratory-based diagnostic techniques. The pyrolysis process is found to be divided into three stages. During a controlled temperature ramp, the selected organic N-C precursor (nicarbazin) began melting and decomposing just below 400 °C, forming a certain number of micrometer-scale pores and pathways. With increase in temperature from 400 °C to 900 °C, amorphous carbon domains started forming, and reduced (metallic) iron nanoclusters appeared, being dispersed uniformly throughout the carbonaceous matrix. When temperature advanced above 900 °C, graphitization of carbon commenced, associated with appearance and evolution of atomically dispersed metal-nitrogen moieties in the carbonaceous matrix. As the graphitization advanced further, a secondary process of agglomeration of metal nanoparticles occurred. Multi-analytical technique observations conducted here provide a base for rational design and optimization of M-N-C electrocatalysts via pyrolysis.
36 MATERIALS SCIENCE↗
Process Optimization and Real-Time Control of Synergistic Microalgae Cultivation and Wastewater Treatment (Final Technical Report)
The overarching goal of this work was to accelerate the commercialization of high productivity, mixed community microalgal treatment technologies for the synergistic treatment of wastewater and the production of biofuel feedstocks. This project addressed a critical barrier to the financial viability and energy efficiency of algal wastewater treatment: an inability to design and operate high-rate processes that reliably achieve target effluent qualities, areal productivities, and biochemical compositions (lipid, protein, carbohydrate content) despite fluctuations in wastewater composition, weather, and microbial communities. Key outcomes from this work include an optimized and controlled Advanced Biological Nutrient Recovery (ABNR) design as well as a suite of open-source tools that include a calibrated and validated algae process simulator in QSDsan and a novel low-cost, real-time microbial monitoring tool. These tools can be leveraged by other algal cultivation and wastewater treatment technology developers in future work.
09 BIOMASS FUELS↗
High Performance Computing to Quantify the Evolution of Microscopic Concentration Gradients During Flash Processing
During the Flash process, the cross section of a plain-carbon or a low-alloy steel is austenitized through rapid heating and transformed on rapid cooling to a predominantly martensite + bainite structure with small amounts of retained austenite. Unlike conventional heat treating, homogeneity is intentionally avoided during Flash processing of steels. The Flash process assembly consists of a pair of rolls that transfer the steel sheets through the heating and cooling stage of the thermal cycle. The initial microstructure of the steel consists of ferrite (body-centered cubic iron) + carbide ((Fe,X)mCn) mixture. The heating rate through the peak temperature is a function of temperature and reaches a peak of about 300-400°C/s and the cooling rate has a maximum value of 3,000-4,000°C/s. The on-heating phase transformations include carbide dissolution, austenite (face-centered cubic iron) nucleation and growth, and diffusion of carbon and other substitutional elements in the steel. The on-cooling phase transformations include formation of martensite (body-centered tetragonal phase containing supersaturated solute) and bainite (ferrite plates with or without fine carbides). In this project, the focus is on Fe-C-Cr steels that are currently Flash processed for armor applications. The modeling effort proposed here will help optimize the Flash thermal cycle for these low alloy steels to achieve the target performance, which is an ongoing effort at SFP Works. A significant feature of Flash processed Fe-C-Cr steels is the presence of scatter in the through-thickness in the sheet. The variability in hardness results from a variability in the bainite + martensite microstructure that is sensitive to the local chemical concentration of C and Cr. Such a chemical inhomogeneity is intentionally obtained in the Flash process. Although such a microstructural gradient is presumably responsible for the exceptional properties of the Flash processed steel, it is very important to quantify the gradients as a function of Flash variabilities in processing parameters and the input microstructure. Understanding the mechanistic pathway that leads to microstructural gradients could be ground-breaking and instrumental for achieving better process control and optimized microstructural state to meet application-specific strength-ductility requirements. Since the final microstructure depends on setting up precise solute concentration gradients through a rapid heating process, and transforming these regions into various phases, it is important to understand how small changes in steel chemistry, input microstructure (carbide size and distribution), and process variables (Flash thermal cycle) will impact the solute concentration gradients.
97 MATHEMATICS AND COMPUTING↗
Directed Energy Deposition Process Modeling, Validation, and Process-Informed Optimization
The directed energy deposition (DED) process, one of the most popular additive manufacturing techniques in use today, involves various complex physical mechanisms that are not yet well understood. In this regard, computational tools show promise for elucidating the manufacturing process and enabling nondestructive performance evaluations of manufactured parts. To better control and optimize the DED process?thereby improving the manufactured product? the present work develops and demonstrates a novel artificial intelligence (AI)-based process control and optimization technique. Specifically, a geometry-free thermo-mechanical model with adaptive subdomain construction is developed to accurately capture the material?s thermo-mechanical response under cyclical reheating and high cooling rates [1]. The model is demonstrated and validated with experimental measurements, in light of various geometries and processing parameters. Moreover, based on this thermo-mechanical model, a physics-informed reduced-order model is developed to enable quick predictions of the temperature field at every time step. Furthermore, an AI-based controller is developed that can adapt to the ever-changing system states by automatically adjusting the manufacturing process parameters. This entire work is based on the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) [2] and its recent integration with Libtorch (the C++ frontend of PyTorch [3]). The combined development of the adaptive material deposition scheme, thermo-mechanical model, associated reduced-order model, and AI-based process controller carries great potential for improving advanced manufacturing processes.
36 MATERIALS SCIENCE↗
Process control integration requirements for advanced life support systems applicable to manned space missions
An overview of recent developments in process-control technology which might have applications in future advanced life support systems for long-duration space operations is presented. Consideration is given to design criteria related to control system selection and optimization, and process-control interfacing methodology. Attention is also given to current life support system process control strategies, innovative sensors, instrumentation and control, and innovations in process supervision.
Spurlock, Paul↗
A quasi-analytical method for non-iterative computation of nonlinear controls
An optimal control solution process was developed for a general class of nonlinear dynamical systems. The method combines control theory, perturbation methods, and Van Loan's recent matrix exponential results. A variety of applications support the practical utility of this method. Nonlinear rigid body optimal maneuvers are routinely solved. Flexible body dynamical systems of an order greater than 40 were solved. The method fails occasionally due to poor convergence of the perturbation expansion or numerical difficulties associated with computing the matrix exponential. The method is attractive because it appears to be a good candidate for semi-automation; no initial guess is required, and it usually converges at 2nd or 3rd order in minutes of machine time.
Junkins, J. L.↗
Revealing the Structural Evolution and Phase Transformation of O3-Type NaNi 1/3 Fe 1/3 Mn 1/3 O 2 Cathode Material on Sintering and Cycling Processes
O-type layered oxide cathode materials can be easily synthesized for a full sodium stoichiometry with high specific capacity, but they all suffer from a capacity fade on cycling. The sintering process control and optimization are critical to ensure a high quality and consistency of the prepared cathode materials with stable structure. Herein, in situ high-energy X-ray diffraction (HEXRD) was first employed to investigate the phase evolution of the oxides during the sintering process of O3-type NaNi 1/3 Fe 1/3 Mn 1/3 O 2 . The in situ HEXRD and both operando Bragg coherent diffraction (BCXD) and coherent multicrystal diffraction (CMCD) were utilized to investigate the phase transformation of the cathode materials during the sodiation/desodiation process. A composite structure comprised of O-type and P-type oxides was formed after the initial electrochemical activation of the cathode material, resulting in good structural and electrochemical stability. This finding implies that strain engineering can be a new design philosophy for the development of next generation high-performance sodium ion cathodes.
25 ENERGY STORAGE↗
Heat Transfer of Thermocapillary Convection in a Two-Layered Fluid System Under the Influence of Magnetic Field
Heat transfer of a two-layer fluid system has been of great importance in a variety of industrial applications. For example, the phenomena of immiscible fluids can be found in materials processing and heat exchangers. Typically in solidification from a melt, the convective motion is the dominant factor that affects the uniformity of material properties. In the layered flow, thermocapillary forces can come into an important play, which was first emphasized by a previous investigator in 1958. Under extraterrestrial environments without gravity, thermocapillary effects can be a more dominant factor, which alters material properties in processing. Control and optimization of heat transfer in an immiscible fluid system need complete understanding of the flow phenomena that can be induced by surface tension at a fluid interface. The present work is focused on understanding of the magnetic field effects on thermocapillary convection, in order to optimize material processing. That is, it involves the study of the complicated phenomena to alter the flow motion in crystal growth. In this effort, the Marangoni convection in a cavity with differentially heated sidewalls is investigated with and without the influence of a magnetic field. As a first step, numerical analyses are performed, by thoroughly investigating influences of all pertinent physical parameters. Experiments are then conducted, with preliminary results, for comparison with the numerical analyses.
Ramachandran, N.↗
Lecture notes on stochastic control, part I
Stochastic control of diffusion processes, optimal linear filtering and prediction, and optimization of control for Markov chains
CONTROL SYSTEM↗
Fast and accurate reduced-order modeling of a MOOSE-based additive manufacturing model with operator learning
One predominant challenge in additive manufacturing (AM) is to achieve specific material properties by manipulating manufacturing process parameters during the runtime. Such manipulation tends to increase the computational load imposed on existing simulation tools employed in AM. The goal of the present work is to construct a fast and accurate reduced-order model (ROM) for an AM model developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, ultimately reducing the time/cost of AM control and optimization processes. Our adoption of the operator learning (OL) approach enabled us to learn a family of differential equations produced by altering process variables in the laser’s Gaussian point heat source. More specifically, we used the Fourier neural operator (FNO) and deep operator network (DeepONet) to develop ROMs for time-dependent responses. Furthermore, we benchmarked the performance of these OL methods against a conventional deep neural network (DNN)-based ROM. Ultimately, we found that OL methods offer comparable performance and, in terms of accuracy and generalizability, even outperform DNN at predicting scalar model responses. The DNN-based ROM afforded the fastest training time. Furthermore, all the ROMs were faster than the original MOOSE model yet still provided accurate predictions. FNO had a smaller mean prediction error than DeepONet, with a larger variance for time-dependent responses. Unlike DNN, both FNO and DeepONet were able to simulate time series data without the need for dimensionality reduction techniques. Finally, the present work can help facilitate the AM optimization process by enabling faster execution of simulation tools while still preserving evaluation accuracy.
36 MATERIALS SCIENCE↗