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At least 163 records · Page 9

Energy efficiency in industrial drying: A hybrid ultrasonic system with a novel dynamic optimization framework

Drying processes are among the most energy-consuming operations in industrial and manufacturing settings, demanding strategic selection, design, and control for enhanced efficiency. Advancing drying technologies is critical for improving sustainability, lowering energy use, reducing carbon emissions, and minimizing waste. This study explores two innovative strategies aimed at transforming drying processes into sustainable, low-carbon systems by reducing energy consumption, minimizing waste, and maintaining a strong emphasis on preserving product quality. The first strategy showcases a sub-pilot scale hybrid ultrasonic-convective dryer for agrifood products. This technology, powered by electricity (process electrification), integrates non-thermal ultrasonic dehydration with convective heating and is presented as a sustainable and energy-efficient solution that enhances eco-friendly practices. The second strategy involves introducing and implementing a novel, multiobjective, mixed integer dynamic optimization technique to determine the optimal time-dependent process parameter values for the drying operation. This optimization technique yields operating conditions that are piecewise constant in time aiming to maximize the energy efficiency of the hybrid ultrasonic-convective dryer while ensuring strict adherence to product quality constraints. By adopting the hybrid ultrasonic-convective dryer, a notable 35% improvement in energy efficiency was achieved compared to conventional hot-air drying systems for drying apple slices. The proposed optimization framework further enhanced energy efficiency by nearly 14% over the most efficient process on the identical testbed, under static operating conditions. The reported enhancements have been experimentally validated. Regarding drying time (thereby improving production yield), the developed hybrid ultrasonic-convective dryer demonstrates as much as a 41% reduction in total processing time, which is further optimized by an additional 10% using our proposed optimization framework. The research outcomes have profound implications for the design and operation of drying systems, encompassing crucial aspects such as process electrification, cost-effectiveness, energy savings, time efficiency, product yield, product quality, and process automation.

Dynamic optimization↗

Human motion planning based on recursive dynamics and optimal control techniques

This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling the motion of articulated figures. A quasi-Newton nonlinear programming technique (super-linear convergence) is implemented to solve minimum torque-based human motion-planning problems. The explicit analytical gradients needed in the dynamics are derived using a matrix exponential formulation and Lie algebra. Cubic spline functions are used to make the search space for an optimal solution finite. Based on our formulations, our method is well conditioned and robust, in addition to being computationally efficient. To better illustrate the efficiency of our method, we present results of natural looking and physically correct human motions for a variety of human motion tasks involving open and closed loop kinematic chains.

Non-NASA Center↗

Selective laser melting of oxide dispersion strengthened MA956 alloy and its surface finishing by magnetic field assisted finishing

Selective laser melting (SLM) is a prominent metal additive manufacturing (AM) capable of processing a myriad of engineering materials with high precision and design freedom. However, similar to other AM processes, poor surface finishing has been an omnipresent problem in SLM technology. In this study, magnetic field assisted finishing (MAF) was used to finish SLM fabricated oxide dispersion strengthened (ODS) MA956, an iron-chromium-aluminum alloy. The effect of laser processing parameters on part density and surface roughness was first studied. Using a multi-objective optimization technique, the optimal parameters to obtain the highest density and lowest surface roughness were determined. Finally, MAF was applied to the parts built with the obtained optimal SLM parameters, but without significant improvement on the surfaces of as-printed samples. Hence, the surfaces of as-printed samples were post-processed (ground) to yield better initial surface conditions prior to MAF. The effect of initial roughness, iron particles size, and abrasive size on MAF performance was studied. Initial roughness had the most dominant effect followed by abrasive size. The underlying mechanism behind the dependency on initial roughness on final surface quality was analyzed by studying the change on the surface profiles with different starting initial roughness. The initial roughness required for MAF to be effective was determined. In conclusion, using the optimal processing conditions, MAF was applied to the post-processed samples to attain the final average surface roughness (R a ) as little as 0.36 μm starting from initial average roughness (R a ) of 1.53 μm.

36 MATERIALS SCIENCE↗

Successes and Opportunities for Discovery of Metal Oxide Photoanodes for Solar Fuels Generators

We report that the importance of metal oxide photoanodes in solar fuels technology has garnered concerted efforts in photoanode discovery in recent decades, which complement parallel efforts in development of analytical techniques and optimization strategies using standard photoanodes such as TiO 2 , Fe 2 O 3 and BiVO 4 . Theoretical guidance of high-throughput experiments has been particularly effective in dramatically increasing the portfolio of metal oxide photoanodes, motivating a new era of photoanode development where the characterization and optimization techniques developed on traditional materials are applied to nascent photoanodes that exhibit visible light photoresponse. The compendium of metal oxide photoanodes presented in the present work can also serve as the basis for further technique development, with a primary goal to establish workflows for discovery of materials that perform better against the critical criteria of operational stability, visible light photoresponse, and photovoltage suitable for tandem absorber architectures.

14 SOLAR ENERGY↗

Optimal placement of tuning masses for vibration reduction in helicopter rotor blades

Described are methods for reducing vibration in helicopter rotor blades by determining optimum sizes and locations of tuning masses through formal mathematical optimization techniques. An optimization procedure is developed which employs the tuning masses and corresponding locations as design variables which are systematically changed to achieve low values of shear without a large mass penalty. The finite-element structural analysis of the blade and the optimization formulation require development of discretized expressions for two performance parameters: modal shaping parameter and modal shear amplitude. Matrix expressions for both quantities and their sensitivity derivatives are developed. Three optimization strategies are developed and tested. The first is based on minimizing the modal shaping parameter which indirectly reduces the modal shear amplitudes corresponding to each harmonic of airload. The second strategy reduces these amplitudes directly, and the third strategy reduces the shear as a function of time during a revolution of the blade. The first strategy works well for reducing the shear for one mode responding to a single harmonic of the airload, but has been found in some cases to be ineffective for more than one mode. The second and third strategies give similar results and show excellent reduction of the shear with a low mass penalty.

Pritchard, Jocelyn I.↗

A Neural Network Aero Design System for Advanced Turbo-Engines

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Sanz, Jose M.↗

Optimal Sensor Allocation for Fault Detection and Isolation

Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

Azam, Mohammad↗

Flight Control Development for the ARH-70 Armed Reconnaissance Helicopter Program

In July 2005, Bell Helicopter won the U.S. Army's Armed Reconnaissance Helicopter competition to produce a replacement for the OH-58 Kiowa Warrior capable of performing the armed reconnaissance mission. To meet the U.S. Army requirement that the ARH-70A have Level 1 handling qualities for the scout rotorcraft mission task elements defined by ADS-33E-PRF, Bell equipped the aircraft with their generic automatic flight control system (AFCS). Under the constraints of the tight ARH-70A schedule, the development team used modem parameter identification and control law optimization techniques to optimize the AFCS gains to simultaneously meet multiple handling qualities design criteria. This paper will show how linear modeling, control law optimization, and simulation have been used to produce a Level 1 scout rotorcraft for the U.S. Army, while minimizing the amount of flight testing required for AFCS development and handling qualities evaluation of the ARH-70A.

Christensen, Kevin T.↗

A technique for optimal temperature estimation for modeling sunrise/sunset thermal snap disturbance torque

A predictive temperature estimation technique which can be used to drive a model of the Sunrise/Sunset thermal 'snap' disturbance torque experienced by low Earth orbiting spacecraft is described. The twice per orbit impulsive disturbance torque is attributed to vehicle passage in and out of the Earth's shadow cone (umbra), during which large flexible appendages undergo rapidly changing thermal conditions. Flexible members, in particular solar arrays, experience rapid cooling during umbra entrance (Sunset) and rapid heating during exit (Sunrise). The thermal 'snap' phenomena has been observed during normal on-orbit operations of both the LANDSAT-4 satellite and the Communications Technology Satellite (CTS). Thermal 'snap' has also been predicted to be a dominant source of error for the TOPEX satellite. The fundamental equations used to model the Sunrise/Sunset thermal 'snap' disturbance torque for a typical solar array like structure will be described. For this derivation the array is assumed to be a thin, cantilevered beam. The time varying thermal gradient is shown to be the driving force behind predicting the thermal 'snap' disturbance torque and therefore motivates the need for accurate estimates of temperature. The development of a technique to optimally estimate appendage surface temperature is highlighted. The objective analysis method used is structured on the Gauss-Markov Theorem and provides an optimal temperature estimate at a prescribed location given data from a distributed thermal sensor network. The optimally estimated surface temperatures could then be used to compute the thermal gradient across the body. The estimation technique is demonstrated using a typical satellite solar array.

Zimbelman, D. F.↗

Rapid macrovoid characterization in membranes prepared via nonsolvent-induced phase separation: A comparison between 2D and 3D techniques

Optimizing the performance of asymmetric membranes prepared via nonsolvent-induced phase separation (NIPS) requires a quantitative understanding of how processing variables influence membrane morphology. Presently, the most useful structural quantification techniques require 3D visualization of the membrane structure and are best suited for studies seeking detailed information on small datasets. This study proposes and validates a rapid and accurate technique for quantifying macroporosity (i.e., D m ), a simple descriptor of sublayer macrovoid content in asymmetric membranes D m . values measured from segmented cross-sectional imaging performed via X-ray computed tomography (XCT) and scanning electron microscopy (SEM) are presented and compared for three asymmetric membranes prepared from commercial polymers. Importantly, analyses of 3D XCT membrane reconstructions reveal that D m is described by a single, centralized mean, which demonstrates that macrovoid content is spatially homogenous. Thus, D m can be approximated from limited sampling of the 2D cross-sectional membrane structure via SEM. A proposed 2D SEM sampling method provides D m estimates within ±6% of corresponding 3D XCT values with 30 independent measurements for the three membranes. Further sensitivity is achieved using complementary descriptors such as macrovoid count density (i.e., C m ). This technique is thus a useful tool for characterizing macroporosity from a broad selection of membrane samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Techniques for optimal crop selection in a controlled ecological life support system

A Controlled Ecological Life Support System (CELSS) utilizes a plant's natural ability to regenerate air and water while being grown as a food source in a closed life support system. Current plant research is directed toward obtaining quantitative empirical data on the regenerative ability of each species of plant and the system volume and power requirements. Two techniques were adapted to optimize crop species selection while at the same time minimizing the system volume and power requirements. Each allows the level of life support supplied by the plants to be selected, as well as other system parameters. The first technique uses decision analysis in the form of a spreadsheet. The second method, which is used as a comparison with and validation of the first, utilizes standard design optimization techniques. Simple models of plant processes are used in the development of these methods.

Mccormack, Ann↗

Techniques for optimal crop selection in a controlled ecological life support system

A Controlled Ecological Life Support System (CELSS) utilizes a plant's natural ability to regenerate air and water while being grown as a food source in a closed life support system. Current plant research is directed toward obtaining quantitative empirical data on the regenerative ability of each species of plant and the system volume and power requirements. Two techniques were adapted to optimize crop species selection while at the same time minimizing the system volume and power requirements. Each allows the level of life support supplied by the plants to be selected, as well as other system parameters. The first technique uses decision analysis in the form of a spreadsheet. The second method, which is used as a comparison with and validation of the first, utilizes standard design optimization techniques. Simple models of plant processes are used in the development of these methods.

Mccormack, Ann↗

Overview on Transactive Energy—Advantages and Challenges for Weak Power Grids

This document lists some challenges that researchers face when implementing transactive energy in weak power grids. These challenges often include high voltage fluctuations, limited generation, high line loadability, and unbalanced grids. The operation of transactive energy, as well as optimization techniques, are also considered, highlighting the performance and functionalities depending on power grid characteristics and market topology. Some of the most used optimization techniques for market clearing, considering the characteristics and topology, are presented as part of the research work. In addition, this paper compares different market topologies and highlights their advantages and challenges. Furthermore, this paper contains a brief description of the interoperability frameworks applied to a smart grid. As a result, it was determined that interoperability is necessary for the proper functioning of the grid. Moreover, all methods were found to be effective for their purpose from the user’s point of view as each technique has different characteristics relevant to the user and the grid. It was concluded that it is convenient to combine the optimization techniques to consider different constraints in the market clearing.

14 SOLAR ENERGY↗

Determining Proton Transport in Pseudo Catalyst Layers Using Hydrogen Pump DC and AC Techniques

Optimizing electrode morphology with a more uniform ionomer distribution is key to reducing ohmic losses and increasing electrocatalyst utilization in polymer electrolyte fuel cells (PEFCs). Inherent ionomer conductivity, volume fraction and tortuosity determine effective ionic conductivity. We use hydrogen pump (HP) method to measure effective ionic conductivity of a pseudo catalyst layer (PCL) comprised of Vulcan XC-72 carbon black and 3M 825 EW ionomer with ionomer to carbon (I/C) ratios of 0.6, 1 and 1.4 and relative humidity (RH) range of 50 to 120%. These direct current (DC) experiments are then compared with electrochemical impedance spectroscopy (EIS). Both DC and EIS methods show good agreement, indicating that EIS can be used as an alternative to DC method in HP experiment. Ionic conductivity for PCL with I/C of 1 and 1.4 was found to be about one order of magnitude higher than I/C of 0.6 for most of the RH range. At 90% RH tortuosities for I/C = 1 and 1.4 were close to 1, whereas tortuosity for I/C = 0.6 was 3. With decrease in relative humidity tortuosities increased linearly and at 50% relative humidity a PCL with I/C = 0.6 had the highest tortuosity of 6.1.

25 ENERGY STORAGE↗

Time-domain technique for optimal design of digital-filter equalizers.

A technique is presented for the design of frequency-sampling and transversal digital filters from specified unit-impulse responses. The multiplier coefficients for the digital filter are specified by the use of a linear-programming algorithm. Examples include the design of digital filters to generate intersymbol-free pulses for data transmission over ideal bandlimited channels and to equalize data transmission channels that have known unit-impulse responses.

Burlage, D. W.↗

A technique for optimizing the design of power semiconductor devices

A technique is described that provides a basis for predicting whether any device design change will improve or degrade the unavoidable trade-off that must be made between the conduction loss and the turn-off speed of fast-switching high-power thyristors. The technique makes use of a previously reported method by which, for a given design, this trade-off was determined for a wide range of carrier lifetimes. It is shown that by extending this technique, one can predict how other design variables affect this trade-off. The results show that for relatively slow devices the design can be changed to decrease the current gains to improve the turn-off time without significantly degrading the losses. On the other hand, for devices having fast turn-off times design changes can be made to increase the current gain to decrease the losses without a proportionate increase in the turn-off time. Physical explanations for these results are proposed.

Schlegel, E. S.↗