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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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At least 667 records · Page 37

Control optimization, stabilization and computer algorithms for aircraft applications

Computationally useful algorithms are considered that can aid the control engineer in designing systems control in linear time invariant dynamics for aircraft applications. Structural aspects of system identification, matrix parameterization, and the effect of feedback on identifiability of systems. Adaptive and stochastic control model constructions are projected, and a method for approximate identification of aircraft characteristics and subsequent generation of control signals is outlined.

Mitter, S. K.↗

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗

Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems (Final Report for AEOLUS)

The AEOLUS Center is dedicated to developing a unified optimization-under-uncertainty framework for: (1) learning predictive models from data; and (2) optimizing experiments, processes, and designs governed by these models, all driven by complex, uncertain energy systems. AEOLUS addresses the critical need for principled, rigorous, scalable, and structure-exploiting capabilities for exploring parameter and decision spaces of complex forward simulation models. This report summarizes the key highlights of our research during the period of performance.

97 MATHEMATICS AND COMPUTING↗

Adjoint-Based Methodology for Time-Dependent Optimal Control (AMTOC)

During the five years of this project, the AMTOC team developed an adjoint-based methodology for design and optimization of complex time-dependent flows, implemented AMTOC in a testbed environment, directly assisted in implementation of this methodology in the state-of-the-art NASA's unstructured CFD code FUN3D, and successfully demonstrated applications of this methodology to large-scale optimization of several supersonic and other aerodynamic systems, such as fighter jet, subsonic aircraft, rotorcraft, high-lift, wind-turbine, and flapping-wing configurations. In the course of this project, the AMTOC team has published 13 refereed journal articles, 21 refereed conference papers, and 2 NIA reports. The AMTOC team presented the results of this research at 36 international and national conferences, meeting and seminars, including International Conference on CFD, and numerous AIAA conferences and meetings. Selected publications that include the major results of the AMTOC project are enclosed in this report.

Yamaleev, Nail↗

Powertrain Controls Optimization for HD Hybrid Line Haul Trucks - FY2014 Annual Report

This is a vehicle system level project, encompassing analytical modeling and supervisory controls development as well as experimental verification/validation testing at the component, powertrain, and full vehicle system level. This project supports the goal of petroleum consumption reduction for medium and heavy trucks through the development of advanced hybrid technologies and control systems. VSST has invested previously in R&D to support hybrid energy storage systems (Li-ion plus ultra-caps) for light duty, passenger car applications. This research will be extended to the MD and HD sector where current battery technology is not mature enough to handle the substantial regenerative braking power levels these trucks are capable of producing. With this hybrid energy storage system, substantial gains in overall vehicle efficiency are possible. In addition, advanced combustion technologies, such as RCCI, will be implemented into an advanced hybrid powertrain for a Class 8 line haul application. This powertrain, leveraged from other VSST work (Meritor, a current ORNL/VSST partner), is ideal for taking advantage of the benefits of RCCI operation due to its series hybrid mode of operation. Emissions control is also a focus of this project, especially due to the fact that RCCI creates a low temperature exhaust stream that must addressed.

33 ADVANCED PROPULSION SYSTEMS↗

Optimal Control of Biomass Feedstock Processing System Under Uncertainty in Biomass Quality

Planning of biorefinery operations is complicated by the stochastic nature of physical and chemical characteristics of biomass feedstock, such as, moisture level and carbohydrate content. Biomass characteristics affect the performance of the equipment which feed the reactor and the efficiency of the conversion process in a biorefinery. We propose a stochastic optimization model to identify a blend of feedstocks, inventory levels, and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor while meeting the requirements of the biochemical conversion process. We propose a sample average approximation (SAA) of the model, and develop an efficient algorithm to solve the SAA model. A feedstock preprocessing process consists of two-stage grinding and pelleting is used to develop a case study. Extensive numerical analysis are conducted which lead to a number of observations. Our main observation is that sequencing bales based on moisture level and carbohydrate content leads to robust solutions that improve processing time and processing rate of the reactor. We provide a number of managerial insights that facilitate the implementation of the model proposed. Note to Practitioners—This paper is motivated by the challenges faced in the bioenergy industry. The focus of this paper is on plants which use the biochemical conversion process to generate liquid fuels. It has been observed that variations in biomass characteristics, such as moisture content, cause variations in feeding of the system which lead to under-utilization of equipment. A requirement of biochemical conversion process is to maintain the carbohydrate content of biomass processed by the reactor, larger than a threshold. We propose a model that identifies the inventory levels and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor. The goal is to improve equipment utilization while satisfying the requirements of the conversion process. The model is tested using real-life data. We found out that by sequencing bales based on moisture level and carbohydrate content, a plant can reduce variability in the system leading to improved system reliability, higher processing rates of the reactor, and higher throughput.

09 BIOMASS FUELS↗

Integrated structure-control optimization of space structures

In the past few years there has been substantial interest in the integrated design of large space structures and their vibration control systems. This paper overviews two aspects of integrated control-structure design. The first is the calculation of derivatives of control system stability margins with respect to structural parameters, and the effect of modal truncation on the accuracy of these derivatives. The second aspect is the various formulations used to define an integrated design optimization problem.

Haftka, Raphael T.↗

ELM control optimization for various ITER scenarios based on linear and quasi-linear figures of merit

For the purpose of better understanding type-I edge localized mode (ELM) control in ITER with resonant magnetic perturbation (RMP) fields, the plasma response to RMP is computed by a resistive full magneto-hydrodynamic model in toroidal geometry. Five scenarios designed for ITER are considered, ranging from the pre-nuclear to nuclear phases. The plasma response to RMP is quantified by the plasma surface displacement near the X-point of the divertor plasma and at the outboard mid-plane. The optimal coil configurations between two high- Q deuterium-tritium (DT) scenarios (at the same plasma current of 15 MA and the same magnetic field of 5.3 T but different fusion gains, Q = 5 and 10) are predicted to be similar. For the other ITER scenarios with similar edge safety factor q 95 ~ 3 to that of the baseline scenario, the optimal coil phasing is also similar. The optimization results are different for a half-current full-field (7.5 MA/5.3 T) scenario, largely due to the difference in q 95 . The RMP coil currents are also optimized to tailor the core vs edge toroidal torques exerted by the 3D RMP fields on the plasma column. Torque optimization, with various objective functions proposed in the study, is useful for minimizing the side effects of RMP on the plasma core flow in ITER, while still maintaining the ELM control capability. Full utilization of three rows of ELM control coils in ITER is found to be essential to ensure both flexibility and robustness of ELM control, in terms of both linear and quasilinear plasma responses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimal control of large space structures via generalized inverse matrix

Independent Modal Space Control (IMSC) is a control scheme that decouples the space structure into n independent second-order subsystems according to n controlled modes and controls each mode independently. It is well-known that the IMSC eliminates control and observation spillover caused when the conventional coupled modal control scheme is employed. The independent control of each mode requires that the number of actuators be equal to the number of modelled modes, which is very high for a faithful modeling of large space structures. A control scheme is proposed that allows one to use a reduced number of actuators to control all modeled modes suboptimally. In particular, the method of generalized inverse matrices is employed to implement the actuators such that the eigenvalues of the closed-loop system are as closed as possible to those specified by the optimal IMSC. Computer simulation of the proposed control scheme on a simply supported beam is given.

Nguyen, Charles C.↗

Approximating the linear quadratic optimal control law for hereditary systems with delays in the control

The fundamental control synthesis issue of establishing a priori convergence rates of approximation schemes for feedback controllers for a class of distributed parameter systems is addressed within the context of hereditary systems. Specifically, a factorization approach is presented for deriving approximations to the optimal feedback gains for the linear regulator-quadratic cost problem associated with time-varying functional differential equations with control delays. The approach is based on a discretization of the state penalty which leads to a simple structure for the feedback control law. General properties of the Volterra factors of Hilbert-Schmidt operators are then used to obtain convergence results for the controls, trajectories and feedback kernels. Two algorithms are derived from the basic approximation scheme, including a fast algorithm, in the time-invariant case. A numerical example is also considered.

Milman, Mark H.↗

Approximating the linear quadratic optimal control law for hereditary systems with delays in the control

The fundamental control synthesis issue of establishing a priori convergence rates of approximation schemes for feedback controllers for a class of distributed parameter systems is addressed within the context of hereditary schemes. Specifically, a factorization approach is presented for deriving approximations to the optimal feedback gains for the linear regulator-quadratic cost problem associated with time-varying functional differential equations with control delays. The approach is based on a discretization of the state penalty which leads to a simple structure for the feedback control law. General properties of the Volterra factors of Hilbert-Schmidt operators are then used to obtain convergence results for the controls, trajectories and feedback kernels. Two algorithms are derived from the basic approximation scheme, including a fast algorithm, in the time-invariant case. A numerical example is also considered.

Milman, Mark H.↗

Optimal Control of a Surge-Mode WEC in Random Waves

The objective of this project was to develop one or more real-time feedback and feed-forward (MPC) control algorithms for an Oscillating Surge Wave Converter (OSWC) developed by RME called SurgeWEC™ that leverages recent innovations in wave energy converter (WEC) control theory to maximize power production in random wave environments. The control algorithms synthesized innovations in dynamic programming and nonlinear wave dynamics using anticipatory wave sensors and localized sensor measurements; e.g. position and velocity of the WEC Power Take Off (PTO), with predictive wave forecasting data. The result was an advanced control system that uses feedback or feed-forward data from an array of sensor channels comprised of both localized and deployed sensors fused into a single decision process that optimally compensates for uncertainties in the system dynamics, wave forecasts, and sensor measurement errors.

16 TIDAL AND WAVE POWER↗

Towards understanding initiation reactions of explosives via ultrafast laser quantum control

Optimal control can be utilized to control the initiation reaction of explosives, where time dependent phase shaped electric fields drive the chemical systems towards a desired state. For quantum controlled initiation (QCI) of explosives a pulse is created which seeks to achieve initiation by employing shaped ultraviolet light. QCI will enhance the understanding of energetic material reactions by yielding insight into the characteristics, such as critical 'hot spot' size and reaction dynamics, necessary for initiation. Quantum control experiments require the ability to: (1) phase and amplitude shape an ultrafast laser pulse, (2) measure the effect of pulse shape, and (3) optimize the desired outcome. Pulse shaping is performed with a 4-focal length dispersed fused silica acousto-optic modulator (AOM) at 400 nm in the ultraviolet (UV). Transient absorption spectroscopy is used to measure the pulse shape effects. Both global and local optimization search routines such as genetic algorithm, differential evolution, and downhill simplex are used to search for the optimal pulse shape. Hexanitroazobenzene (HNAB), Trinitroanaline (TNA) and Diaminoazozyfurazan (DAAF) are excited to the first electronic state with 400 nm light. Our initiation experiments are studying the effect of phase shaped 400 nm pulses on HNAB, TNA and DAAF. Novel transient absorption spectra for each material have been obtained and note worthy regions further investigated with single parameter control (second order spectral phase and energy). Many systems have simple intensity control such as that shown by DAAF. TNA and HNAB have spectral features that are not single parameter driven and are being further investigated with complex control.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Optimal control of lift/drag ratios on a rotating cylinder

We present the numerical solution to a problem of maximizing the lift to drag ratio by rotating a circular cylinder in a two-dimensional viscous incompressible flow. This problem is viewed as a test case for the newly developing theoretical and computational methods for control of fluid dynamic systems. We show that the time averaged lift to drag ratio for a fixed finite-time interval achieves its maximum value at an optimal rotation rate that depends on the time interval.

Ou, Yuh-Roung↗

An Energy Storage Assessment: Using Optimal Control Strategies to Capture Multiple Services

This paper presents a methodology for evaluating benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. In the proposed method, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This methodology is used to assess energy storage alternatives in Puget Sound Energy System. Different battery storage candidates are simulated for a period of one year to assess different value streams and overall benefits, as part of a financial feasibility evaluation of battery storage projects.

Power system economics, energy storge system, batt↗

Online Optimal Control of Connected Vehicles for Efficient Traffic Flow at Merging Roads

This paper addresses the problem of coordinating online connected vehicles at merging roads to achieve a smooth traffic flow without stop-and-go driving. We present a framework and a closed-form solution that optimize the acceleration profile of each vehicle in terms of fuel economy while avoiding collision with other vehicles at the merging zone. The proposed solution is validated through simulation and it is shown that coordination of connected vehicles can reduce significantly fuel consumption and travel time at merging roads.

Autonomous Vehicles↗

Optimal Control of Connected and Automated Vehicles at Roundabouts

Connectivity and automation in vehicles provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better operating decisions to improve safety and reduce pollution, energy consumption, and travel delays. This study investigates the implications of optimally coordinating vehicles that are wirelessly connected to each other and to an infrastructure in roundabouts to achieve a smooth traffic flow without stop-and-go driving. We apply an optimization framework and an analytical solution that allows optimal coordination of vehicles for merging in such traffic scenario. The effectiveness of the efficiency of the proposed approach is validated through simulation and it is shown that coordination of vehicles can reduce total travel time by 3~49% and fuel consumption by 2~27% with respect to different traffic levels. In addition, network throughput is improved by up to 25% due to elimination of stop-and-go driving behavior.

Zhao, Liuhui↗