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At least 1,513 records · Page 84

Reactive Collision Avoidance Algorithm

The reactive collision avoidance (RCA) algorithm allows a spacecraft to find a fuel-optimal trajectory for avoiding an arbitrary number of colliding spacecraft in real time while accounting for acceleration limits. In addition to spacecraft, the technology can be used for vehicles that can accelerate in any direction, such as helicopters and submersibles. In contrast to existing, passive algorithms that simultaneously design trajectories for a cluster of vehicles working to achieve a common goal, RCA is implemented onboard spacecraft only when an imminent collision is detected, and then plans a collision avoidance maneuver for only that host vehicle, thus preventing a collision in an off-nominal situation for which passive algorithms cannot. An example scenario for such a situation might be when a spacecraft in the cluster is approaching another one, but enters safe mode and begins to drift. Functionally, the RCA detects colliding spacecraft, plans an evasion trajectory by solving the Evasion Trajectory Problem (ETP), and then recovers after the collision is avoided. A direct optimization approach was used to develop the algorithm so it can run in real time. In this innovation, a parameterized class of avoidance trajectories is specified, and then the optimal trajectory is found by searching over the parameters. The class of trajectories is selected as bang-off-bang as motivated by optimal control theory. That is, an avoiding spacecraft first applies full acceleration in a constant direction, then coasts, and finally applies full acceleration to stop. The parameter optimization problem can be solved offline and stored as a look-up table of values. Using a look-up table allows the algorithm to run in real time. Given a colliding spacecraft, the properties of the collision geometry serve as indices of the look-up table that gives the optimal trajectory. For multiple colliding spacecraft, the set of trajectories that avoid all spacecraft is rapidly searched on-line. The optimal avoidance trajectory is implemented as a receding-horizon model predictive control law. Therefore, at each time step, the optimal avoidance trajectory is found and the first time step of its acceleration is applied. At the next time step of the control computer, the problem is re-solved and the new first time step is again applied. This continual updating allows the RCA algorithm to adapt to a colliding spacecraft that is making erratic course changes.

Scharf, Daniel↗

Radiograph and passive data analysis using mixed variable optimization

Disclosed herein are representative embodiments of methods, apparatus, and systems for performing radiography analysis. For example, certain embodiments perform radiographic analysis using mixed variable computation techniques. One exemplary system comprises a radiation source, a two-dimensional detector for detecting radiation transmitted through a object between the radiation source and detector, and a computer. In this embodiment, the computer is configured to input the radiographic image data from the two-dimensional detector and to determine one or more materials that form the object by using an iterative analysis technique that selects the one or more materials from hierarchically arranged solution spaces of discrete material possibilities and selects the layer interfaces from the optimization of the continuous interface data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Influence of structural and aerodynamic modeling on optimization with flutter constraint

The influences of structural and aerodynamic modeling on multidisciplinary optimization in an aeroelastic environment are not well understood. Therefore, optimizations with flutter and frequency constraints were performed to investigate the effects these modeling factors have on various representative wings. To this end, the Automated Structural Optimization System (ASTROS) was used as a tool to minimize the weight of various fully built-up finite element wing models in subsonic and supersonic flow under given flutter and frequency constraints. First, the performance of the optimization module was tested against results from other codes on a straight and uniform wing widely used for optimization with flutter constraints. Then, fully built-up finite element models of various wings with different aspect ratios were investigated for the influence on the structural optimization for minimum weight of the following modeling factors: finite element selection, structural grid refinement; number of selected modes, retention of breathing modes; selection of reduced frequencies to be used in flutter analysis; aerodynamic panel size and placement; splining of the aerodynamic grid to the structural grid selection of extra points of the structural wing box for splining; and number of constraints to be retained. Knowledge of these influences as well as of the program behavior is important, since optimization can be made more efficient by the selection of reasonable initial models. Also, it was shown previously that modeling has an impact on the results of modal and aeroelastic analyses. Thus, if modeling errors can negatively affect the analyses, a minimum weight optimization can be jeopardized and result in an optimal design that is rather unreliable. In the following, selected results are presented and the influences of some modeling parameters on optimization are pointed out.

Striz, Alfred G.↗

Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.

42 ENGINEERING↗

Universal and versatile morphology engineering via hot fluorous solvent soaking for organic bulk heterojunction

After explosive growth of efficiency in organic solar cells (OSCs), achieving ideal morphology of bulk heterojunction remains crucial and challenging for advancing OSCs into consumer market. Herein, by utilizing the amphiphobic nature and temperature-dependent miscibility of fluorous solvent, hot fluorous solvent soaking method is developed to optimize the morphology with various donor/acceptor combinations including polymer/small-molecule, all-polymer and all-small-molecule systems. By immersing blend film into hot fluorous solvent which is utilized as liquid medium with better thermal conductivity, the molecular reorganization is accelerated. Furthermore, fluorous solvent can be miscible with the residue of chloroform and chloronaphthalene above upper critical solution temperature. This mixed solvent diffuses around inside the active layer and selectively promotes molecular reorganization, leading to optimized morphology. Compared to widely-used thermal annealing, this approach processed under mild conditions achieves superior photovoltaic performance, indicating the practicality and universality for morphological optimization in OSCs as well as other optoelectronic devices.

14 SOLAR ENERGY↗

Progress Towards Developing Neutron Tolerant Magnetostrictive and Piezoelectric Transducers

Current generation light water reactors (LWRs), sodium cooled fast reactors (SFRs), small modular reactors (SMRs), and next generation nuclear plants (NGNPs) produce harsh environments in and near the reactor core that can severely tax material performance and limit component operational life. To address this issue, several Department of Energy Office of Nuclear Energy (DOE-NE) research programs are evaluating the long duration irradiation performance of fuel and structural materials used in existing and new reactors. In order to maximize the amount of information obtained from Material Testing Reactor (MTR) irradiations, DOE is also funding development of enhanced instrumentation that will be able to obtain in-situ, real-time data on key material characteristics and properties, with unprecedented accuracy and resolution. Such data are required to validate new multi-scale, multi-physics modeling tools under development as part of a science-based, engineering driven approach to reactor development. It is not feasible to obtain high resolution/microscale data with the current state of instrumentation technology. However, ultrasound-based sensors offer the ability to obtain such data if it is demonstrated that these sensors and their associated transducers are resistant to high neutron flux, high gamma radiation, and high temperature. To address this need, the Advanced Test Reactor National Scientific User Facility (ATR-NSUF) is funding an irradiation, led by PSU, at the Massachusetts Institute of Technology Research Reactor to test the survivability of ultrasound transducers. As part of this effort, PSU and collaborators have designed, fabricated, and provided piezoelectric and magnetostrictive transducers that are optimized to perform in harsh, high flux, environments. Four piezoelectric transducers were fabricated with either aluminum nitride, zinc oxide, or bismuth titanate as the active element that were coupled to either Kovar or aluminum waveguides and two magnetostrictive transducers were fabricated with Remendur or Galfenol as the active elements. Pulse-echo ultrasonic measurements of these transducers are made in-situ. This paper will present an overview of the test design including selection criteria for candidate materials and optimization of test assembly parameters, data obtained from both out-of-pile and in-pile testing at elevated temperatures, and an assessment based on initial data of the expected performance of ultrasonic devices in irradiation conditions

Reinhardt1, Brian↗

Aeroelastic Trim Drag Optimization of Mach 0.8 Transonic Truss-Braced Wing Aircraft using High-Lift Devices and Control Surfaces

This paper presents an aeroelastic trim drag optimization study of the Mach 0.8 Transonic Truss-Braced Wing (TTBW) aircraft using the High-lift devices and control surfaces. An aero-structural analysis solver VSPAERO with transonic small disturbance, integral boundary-layer, and wing-strut interference corrections coupled to mode shapes computed by NASTRAN using the Galerkin method is developed to provide a rapid aircraft aeroelastic performance evaluation. Three different flight conditions corresponding to Mach 0.8 are selected for the aeroelastic trim drag optimization at the design and off-design cruise lift coefficients. The preliminary optimization results show that the TTBW aircraft with the optimized deflection of the high-lift devices and control surfaces achieves a drag reduction of about 8.2 counts, 6.5 counts, and 9.7 counts corresponding to the lift coefficients 0.661, 0.695, and 0.729, respectively. A high-fidelity CFD solver FUN3D is used to verify the aeroelastic trim drag optimization.

TTBW↗

Overhead longwave infrared hyperspectral material identification using radiometric models

Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help mitigate false positives. A material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms is presented. The algorithms utilize unwhitened radiance data and Nelder–Meade numerical optimization to estimate the temperature, humidity, and ozone levels of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian information criteria for model selection. The resulting identification product includes an optimal atmospheric profile and a full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing the model parameters to improve identification is also presented. Furthermore, several examples are provided using modeled data at several noise levels.

58 GEOSCIENCES↗

Cleanser, Detergent, Personal Care Product Pretreatment Evaluation

The purpose of the Cleanser, Detergent, Personal Care Product, and Pretreatment Evaluation & Selection task is to identify the optimal combination of personal hygiene products, crew activities, and pretreatment strategies to provide the crew with sustainable life support practices and a comfortable habitat. Minimal energy, mass, and crew time inputs are desired to recycle wastewater during long duration missions. This document will provide a brief background on the work this past year supporting the ELS Distillation Comparison Test, issues regarding use of the hygiene products originally chosen for the test, methods and results used to select alternative products, and lessons learned from testing.

Adam, Niklas↗

Cleanser, Detergent, Personal Care Product, and Pretreatment Evaluation

The purpose of the Cleanser, Detergent, Personal Care Product, and Pretreatment Evaluation & Selection task is to identify the optimal combination of personal hygiene products, crew activities, and pretreatment strategies to provide the crew with sustainable life support practices and a comfortable habitat. Minimal energy, mass, and crew time inputs are desired to recycle wastewater during long duration missions. This document will provide a brief background on the work this past year supporting the ELS Distillation Comparison Test, issues regarding use of the hygiene products originally chosen for the test, methods and results used to select alternative products, and lessons learned from testing.

Adam, Niklas↗

SU-E-T-230: Creating a Large Number of Focused Beams with Variable Patient Head Tilt to Improve Dose Fall-Off for Brain Radiosurgery

Purpose: To develop a treatment delivery and planning strategy by increasing the number of beams to minimize dose to brain tissue surrounding a target, while maximizing dose coverage to the target. Methods: We analyzed 14 different treatment plans via Leksell PFX and 4C. For standardization, single tumor cases were chosen. Original treatment plans were compared with two optimized plans. The number of beams was increased in treatment plans by varying tilt angles of the patient head, while maintaining original isocenter and the beam positions in the x-, y- and z-axes, collimator size, and beam blocking. PFX optimized plans increased beam numbers with three pre-set tilt angles, 70, 90, 110, and 4C optimized plans increased beam numbers with tilt angles increasing arbitrarily from range of 30 to 150 degrees. Optimized treatment plans were compared dosimetrically with original treatment plans. Results: Comparing total normal tissue isodose volumes between original and optimized plans, the low-level percentage isodose volumes decreased in all plans. Despite the addition of multiple beams up to a factor of 25, beam-on times for 1 tilt angle versus 3 or more tilt angles were comparable (<1 min.). In 64% (9/14) of the studied cases, the volume percentage decrease by >5%, with the highest value reaching 19%. The addition of more tilt angles correlates to a greater decrease in normal brain irradiated volume. Selectivity and coverage for original and optimized plans remained comparable. Conclusion: Adding large number of additional focused beams with variable patient head tilt shows improvement for dose fall-off for brain radiosurgery. The study demonstrates technical feasibility of adding beams to decrease target volume.

60 APPLIED LIFE SCIENCES↗

Tailored CO 2 -philic Gas Separation Membranes via One-Pot Thiol–ene Chemistry

Recently, thiol–ene chemistry attracts much attention in the construction of functional polymer materials due to its versatility and fast reaction kinetics, though only a few studies have been reported on its utilization in the fabrication of elastic polymer materials. Herein, a series of elastic, poly(dimethylsiloxane)–poly(ethylene glycol) methyl ether acrylate (PDMS–PEGMEA)-based co-polymer membranes are synthesized via a one-pot thiol–ene reaction. These membranes are highly stable and exhibit tunable thermal/mechanical properties by tailoring the cross-linker and side-chain functionality. When used for gas separation application, all grafted elastomer membranes show excellent gas permeability and selectivity, and the membrane with an optimal composition (PDMS–PEGMEA 30 –EOPDMS 10 ) has reached the Robeson upper bound (CO 2 permeability ~800 barrer and α[CO 2 /N 2 ] ~39). The high permeability originates from the extremely fast chain mobility of PDMS molecules at the ambient temperature. Tailoring the PEGMEA content allows control of the α[CO 2 /N 2 ] ranging from 21 to 39 by enhancing gas solubility within the membrane matrix. This study provides a promising strategy to be utilized for the gutter layer, selective layer, or their combination in the industrial gas separation modules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Continuous-flow reactor with superior production rate and stability for CO 2 reduction using semiconductor photocatalysts

Semiconductor photocatalyst approaches for solar CO 2 reduction are attractive due to their simplicity but have lagged in efficiency compared to less-integrated photoelectrochemical (PEC) approaches and to electrolysis reactors. We identify poor mass transport and catalyst deactivation as key constraints. To address them, we have developed a continuous-flow photocatalytic reactor system allowing us to control the triple-phase interface on the photocatalyst surface using the liquid and reactant gas flow rates. With the goal of selectively producing CO, the reactor is optimized by controlling the pressure and flow rates of the reactant gas and electrolyte in contact with both sides with the intermediately placed catalyst. In comparison to batch reactors with an immobile photocatalyst bed and gas phase CO 2 or CO 2 purged water, 10–24 times higher production rates are achieved for photocatalysts such as TiO 2 , ZnO, C 3 N 4 , and CdS by simply changing to the designed flow-type photoreactor without any catalyst modification. In addition, CO selectivity (93.2%) and long-term stability (>780 min) using the designed reactor are significantly enhanced compared to using the batch reactors (71.7%, <180 min for reduced 50% activity). Here, we propose that the enhanced mass transport on the photocatalyst surface accelerates the desorption of the initial photolysis product, CO, and prevents the poisoning effect from deactivating photocatalyst activity. This study has the potential to facilitate the utilization of semiconductor-based photocatalytic reactions for achieving superior performance wih gaseous reactants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying public perceptions on the nuclear fuel cycle - 15395

The nuclear fuel cycle in the United States, specifically the back end portion, remains an unresolved and persistent issue. In comparison with the technical aspects of many different fuel cycles, less attention has been given to public perceptions and attitudes toward certain alternatives. Understanding what the general public values in terms of a nuclear fuel cycle will assist in selecting a nuclear fuel cycle that optimizes the balance between technical feasibility and public acceptance. A multi-criteria decision analysis (MCDA) model was created to incorporate the general public's perceptions on qualified individuals and on important technical and non-technical aspects of any general fuel cycle. Analyzing the pair-wise comparisons for each criterion through the Analytic Hierarchy Process (AHP) yielded the relative importance of each aspect. A major finding is that the general public tend to view environmental scientists as qualified as nuclear engineers and scientists in selecting a method of used nuclear fuel disposal for the United States. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Cummins MD & HD Accessory Hybridization CRADA -Annual Report FY15

There are many areas of MD and HD vehicles that can be improved by new technologies and optimized control strategies. Component optimization and idle reduction need to be addressed, this is best done by a two part approach that includes selecting the best component technology, and/or architecture, and optimized controls that are vehicle focused. While this is a common focus in the light duty industry it has been gaining momentum in the MD and HD market as the market gets more competitive and the regulations become more stringent. When looking into systems optimization and idle reduction technologies, affected vehicle systems must first be considered, and if possible included in the new architecture to get the most benefit out of these new capabilities. Typically, when looking into idle reduction or component optimization for MD/HD, the vehicle s accessories become a prime candidate for electrification or hybridization. While this has already been studied on light duty vehicles (especially on hybrids and electric vehicles) it has not made any head way or market penetration in most MD and HD applications. If hybrids and electric MD and HD vehicles begin to break into the market this would be a necessary step into the ability to make those vehicles successful by allowing for independent, optimized operation separate from the engine.

33 ADVANCED PROPULSION SYSTEMS↗

Maximum life spiral bevel reduction design

Optimization is applied to the design of a spiral bevel gear reduction for maximum life at a given size. A modified feasible directions search algorithm permits a wide variety of inequality constraints and exact design requirements to be met with low sensitivity to initial values. Gear tooth bending strength and minimum contact ratio under load are included in the active constraints. The optimal design of the spiral bevel gear reduction includes the selection of bearing and shaft proportions in addition to gear mesh parameters. System life is maximized subject to a fixed back-cone distance of the spiral bevel gear set for a specified speed ratio, shaft angle, input torque, and power. Significant parameters in the design are: the spiral angle, the pressure angle, the numbers of teeth on the pinion and gear, and the location and size of the four support bearings. Interpolated polynomials expand the discrete bearing properties and proportions into continuous variables for gradient optimization. After finding the continuous optimum, a designer can analyze near optimal designs for comparison and selection. Design examples show the influence of the bearing lives on the gear parameters in the optimal configurations. For a fixed back-cone distance, optimal designs with larger shaft angles have larger service lives.

Savage, M.↗

Optimal Wind Power Uncertainty Intervals for Electricity Market Operation

It is important to select an appropriate uncertainty level of the wind power forecast for power system scheduling and electricity market operation. Traditional methods hedge against a predefined level of wind power uncertainty, such as a specific confidence interval or uncertainty set, which leaves the questions of how to best select the appropriate uncertainty levels. To bridge this gap, this paper proposes a model to optimize the forecast uncertainty intervals of wind power for power system scheduling problems, with the aim of achieving the best trade-off between economics and reliability. Then we reformulate and linearize the models into a mixed integer linear programming (MILP) without strong assumptions on the shape of the probability distribution. In order to invest the impacts on cost, reliability, and prices in a electricity market, we apply the proposed model on a twosettlement electricity market based on a six-bus test system and on a power system representing the U.S. state of Illinois. The results show that the proposed method can not only help to balance the economics and reliability of the power system scheduling, but also help to stabilize the energy prices in electricity market operation.

electricity market↗