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At least 1,009 records · Page 56

Deterministic optimal maneuver strategy for multi-target missions

This paper presents an optimal strategy for making impulsive correction to a multi-target trajectory by a single maneuver. The concept of an optimal maneuver time is introduced. The choice of suitable weighting functions is explored to enable one to properly translate the subjective desire of mission success into an objective cost function whose minimization yields the optimal strategy. It is shown that a number of strategies previously formulated are derivable from one general expression. A number of other interesting properties of the optimal strategy are described. Numerical results are presented for a typical two-target mission. It is shown that the strategy formulated is optimal. For some perturbations, there exists an optimal maneuver time different from the time of initiation of the perturbation. That is, the physical properties of the trajectory can be exploited to select the optimal time of making a corrective maneuver.

Dwivedi, N. P.↗

Solar/Thermal Powerplant Simulation

Simulation program evaluates performances and energy costs of diverse solar/thermal powerplant configurations. Approach based on optimizing sizes of collector and storage subsystems to give minimum energy cost for specified plant rating and load factor. Methodology provides for consistent comparative evaluation of solar/thermal powerplants.

Bowyer, J. M.↗

Flight Planning

Seagull Technology, Inc., Sunnyvale, CA, produced a computer program under a Langley Research Center Small Business Innovation Research (SBIR) grant called STAFPLAN (Seagull Technology Advanced Flight Plan) that plans optimal trajectory routes for small to medium sized airlines to minimize direct operating costs while complying with various airline operating constraints. STAFPLAN incorporates four input databases, weather, route data, aircraft performance, and flight-specific information (times, payload, crew, fuel cost) to provide the correct amount of fuel optimal cruise altitude, climb and descent points, optimal cruise speed, and flight path.

Source record↗

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗

The use of CMAC neural architectures in obstacle avoidance

In this paper, CMAC neural architectures are used in conjunction with a hierarchical planning approach to find collision free paths over two dimensional analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array.

Peterson, James K.↗

Decentralized Carrier Phase Shifting for Optimal Harmonic Minimization in Asymmetric Parallel-Connected Inverters

This paper presents a carrier phase shifting technique for minimizing the aggregate harmonics in networks of asymmetric parallel-connected inverters for distributed power generation system applications. The proposed technique is: 1) implemented in a decentralized manner, relying only on local voltage and current measurements, and 2) optimal in the sense that it minimizes a cost function representing the carrier-frequency current harmonics. The analysis indicates that the proposed optimal carrier phase shifting technique can enable order-of-magnitude reductions in harmonic power, and also universal improvements compared to symmetric carrier interleaving for asymmetric inverter networks. Moreover, compared to existing methods that require either centralized communication or information exchange between inverters to coordinate carriers, the proposed technique is completely decentralized, which provides important practical benefits for implementation, including improved robustness and reduced cost. The technique is experimentally validated on a network of three single-phase 2-kW inverters and demonstrates a 36.5% reduction in the weighted total harmonic distortion factor of the aggregate inverter current, and the ability to converge to the optimal carrier phase spacing dynamically in less than one line frequency cycle (16.7 ms) in steady state and transient operating conditions.

42 ENGINEERING↗

An overview of the current state of the art optimization used for trajectory design in the GTS system

The high cost of delivering payloads to orbit demands that launch vehicles be flown in an optimal and reliable manner. Thus, computer simulated trajectories are optimized to obtain maximum vehicle payload capability or a maximum amount of reserve fuel, subject to design constraints. The Generalized Trajectory Simulation (GTS) system developed at The Aerospace Corporation is capable of simulating and optimizing trajectories for a wide variety of boost and reentry problems. Optimization is an integral part of the GTS system. This has resulted in progressive use of optimization. Additionally, the flexibility of the GTS system allows optimum trade studies to be conducted and complicated missions to be designed. This paper describes the integrated and flexible nature of the optimization software in the GTS system. Special features of the NLP2 and NLP3 optimization codes are described. Post optimality, parameter sensitivity analysis and the automatic scaling capability in the GTS system are also described.

Beltracchi, Todd J.↗

U.S. Domestic Small Modular Reactor Security by Design

U.S. nuclear power facilities face increasing challenges in meeting evolving security requirements caused by evolving and expanding threats while keeping cost reasonable to make nuclear energy competitive. The addition of security features after a facility has been designed and without attention to optimization (the past approach) can lead to cost overruns. Incorporating security in the design process can provide robust, cost effective, and sufficient physical protection systems. The purpose of this work is to develop a framework for the integration of security into the design phase of Small Modular Reactors (SMRs) and the use of modeling and simulation tools to optimize the design of physical protection systems. This effort will intend to integrate security into the design phase of a model SMR that meets current NRC physical protection requirements and provide advanced solutions to improve physical protection and decrease costs. A suite of tools, including SCRIBE3D, PATHTRACE and Blender were used to model a hypothetical generic domestic SMR facility. Physical protection elements such as sensors, cameras, portal monitors, barriers, and guard forces were added to the model based on best practices for physical protection systems. One outsider sabotage scenario was examined with 4-8 adversaries to determine security metrics. This work will influence physical protection system designs and facility designs for U.S. domestic SMRs. The purpose of this project is to demonstrate how a series of experimental and modeling capabilities across the Department of Energy Complex can impact the design of U.S. domestic SMRs and the complete Safeguards and Security by Design (SSBD) for SMRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Green, Fire–Retarding Ether Solvent for Sustainable High–Voltage Li–Ion Batteries at Standard Salt Concentration

Lithium-ion batteries (LIBs) are increasingly encouraged to enhance their environmental friendliness and safety while maintaining optimal energy density and cost-effectiveness. Although various electrolytes using greener and safer glyme solvents have been reported, the low charge voltage (usually lower than 4.0 V vs Li/Li + ) restricts the energy density of LIBs. Herein, tetraglyme, a less-toxic, non-volatile, and non-flammable ether solvent, is exploited to build safer and greener LIBs. It is demonstrated that ether electrolytes, at a standard salt concentration (1 m), can be reversibly cycled to 4.5 V vs Li/Li + . Anchored with Boron-rich cathode-electrolyte interphase (CEI) and mitigated current collector corrosion, the LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathode delivers competitive cyclability versus commercial carbonate electrolytes when charged to 4.5 V. Synchrotron spectroscopic and imaging analyses show that the tetraglyme electrolyte can sufficiently suppress the overcharge behavior associated with the high-voltage electrolyte decomposition, which is advantageous over previously reported glyme electrolytes. The new electrolyte also enables minimal transition metal dissolution and deposition. NMC811||hard carbon full cell delivers excellent cycling stability at C/3 with a high average Coulombic efficiency of 99.77%. In conclusion, this work reports an oxidation-resilient tetraglyme electrolyte with record-high 4.5 V stability and enlightens further applications of glyme solvents for sustainable LIBs by designing Boron-rich interphases.

36 MATERIALS SCIENCE↗

An Integrated Computational Materials Engineering (ICME) Approach to Design Nonlinear Transition Zones Between Dissimilar Metals

Current approaches to designing graded transition joints (GTJs) between dissimilar metals often rely on linear changes in both composition profiles and thickness of each sublayer. This increases fabrication cost and may not be optimal with respect to residual stress or the formation of undesirable phases. Here, in this study, GTJs between P91 ferritic/martensitic steel and 347H austenitic stainless steel were designed using Integrated Computational Materials Engineering (ICME) principles with nonlinear composition and length profiles. Guided by inputs from classical mechanics and CALPHAD predictions of carbon chemical potential, a novel transition zone consisting of five discrete compositions was proposed, with the thickness of each sublayer varying according to a brachistochrone-inspired distribution. In addition to carbon potential gradients, CALPHAD was used to predict coefficients of thermal expansion, which were incorporated into finite element models to evaluate stress evolution. The proposed nonlinear design resulted in a smoother carbon potential gradient, lower carbon depletion at the P91 interface, and a comparable residual stress under long-term thermal exposure, compared to a conventional linear design using ten sublayers with equal thickness. This work introduces a brachistochrone-inspired distribution for GTJ design, offering a general framework for optimizing graded interfaces between dissimilar metals.

Directed Energy Deposition↗

Opportunities for bioenergy crops to support transitions from irrigated agriculture and conserve the U.S. High Plains Aquifer

This study investigates potential economic and groundwater driven transitions from irrigated maize production—the dominant irrigated cropping system in the High Plains Aquifer (HPA) region—to alternative crops such as sorghum and switchgrass, two common bioenergy feedstocks. Unsustainable groundwater extraction in the U.S. High Plains presents critical challenges including reduced irrigation capacities, diminished crop yields, lower land values, and escalating energy costs. Using a spatially explicit optimization framework combined with comprehensive economic and hydrogeological data, we evaluate optimal land-use strategies and irrigation system investments over a 30-year planning period. Results indicate significant regional variability in the future economic viability of irrigated agriculture, driven by differences in aquifer recharge rates, groundwater availability, and market conditions. Nebraska and parts of northern Texas can sustain irrigated maize profitability due to relatively favorable groundwater conditions and lower land rents, respectively. In contrast, many portions of Kansas and southern Texas are more likely to transition to dryland agriculture within two decades. Colorado and New Mexico show potential for significant adoption of switchgrass production as an alternative biomass-based energy crop. Overall, over the 30-year horizon, our model implies that approximately 23% of currently irrigated maize area across the HPA region may transition to dryland farming under business-as-usual conditions. This transition is complemented by a threefold increase in non-irrigated sorghum production, from 0.20 to 0.77 Mt yr−1, indicating that groundwater-driven shifts in agricultural production may support a larger regional base for bioenergy feedstocks. The study also reveals opportunities for producers to optimize economic returns and biomass production potential.

60 APPLIED LIFE SCIENCES↗

Constructing efficient CuO x -CeO 2 catalyst for NO reduction by CO: New insights into the structure–activity relationship

CuO-CeO 2 based materials have been recognized as promising substitutes for precious metal catalysts in emission control field due to their superior redox property and low cost. In this work, by optimizing the deposition process of CeO 2 and CuO onto γ-Al 2 O 3 , highly dispersed CuO clusters on unique CeO 2 -Al 2 O 3 support with small CeO 2 particles (7Cu-Ce/CeAl) were successfully constructed for efficient NO reduction by CO, which exhibited much higher NO removal efficiency and N 2 selectivity than CuO catalysts supported on γ-Al 2 O 3 (7Cu/Al) and conventional CeO 2 -Al 2 O 3 support (7Cu/CeAl). Moreover, H 2 O showed limited inhibition effect on the catalytic performance of 7Cu-Ce/CeAl catalyst. With the help of Raman spectra, X-ray absorption spectroscopy, in situ diffuse reflectance infrared Fourier transform spectroscopy, etc., it was clearly revealed that the abundant Cu + /Ce 3+ paired sites with surface synergetic oxygen vacancies (SSOV) on 7Cu-Ce/CeAl catalyst could effectively facilitate the adsorption and activation of CO and NO, thus significantly enhancing the NO removal efficiency.

36 MATERIALS SCIENCE↗

Opening twisted polymer chains for simultaneously high printability and battery fast-charge

Fast-charging is key to the widespread adoption of battery-based electric vehicles. However, improving fast-charging through architecture optimization is expensive. To reduce costs and expand to commercialization, we applied roll-to-roll screen printing technology to create channels and decrease the tortuosity of electrodes. For the first time, this work successfully opened twisted polymer chains within high-solid-content inks to improve their screen printability and battery performance of as-printed electrodes. With LiNi 0.6 Mn 0.2 Co 0.2 O 2 as active materials, the 60% solid content ink presents superior screen printability after opening the twisted binder chains. As-printed electrode exhibits 33% higher charge capacity at 6 C than printed electrode with chains twisted ink at mass loading of 6.5 mg/cm 2 . Furthermore, coarse-grained molecular dynamics simulations are performed to study the underlying mechanism systematically. In conclusion, the new ink preparation procedure provides a scalable, effective strategy for manufacturing screen-printable battery ink and promotes screen-printed electrode technology.

25 ENERGY STORAGE↗

Composite biopolymer electrolytes for high-performance reversible zinc-air batteries

Zinc-air batteries (ZABs) are regarded as one of the most promising candidates for next-generation energy storage systems due to their inherent safety, high energy density, and low cost. In this study, we optimized the composition of gel polymer electrolytes (GPEs), which play a crucial role in enhancing ZAB reversibility due to their water retention capabilities. The GPEs are synthesized using a combination of polyacrylic acid (PAA), polyacrylamide (PAM), and biopolymer kappa-carrageenan (KC), with and without additional additives. Among these, the composite GPE containing KC, PAA, and PAM demonstrated superior ionic conductivity (6.68 mS/cm at 30 °C) and enhanced water retention compared to the PAA–PAM-based GPE. Furthermore, this composite electrolyte operates within a wider electrochemical window of −1.0 V–2.2 V. A bifunctional catalyst, nickel–iron layered double hydroxide (NiFe-LDH), is electrochemically synthesized on a modified activated carbon cloth (CC). The catalyst loading is optimized based on oxygen evolution reaction (OER) performance, showing an overpotential of 555 mV. The oxygen reduction reaction (ORR) occurred at a half-wave potential of 0.620 V, which is lower than that of Pt/C (0.852 V), indicating better catalytic activity. The KC based cell exhibit better cycling stability than PAA–PAM-based GPE. The electrochemical performance of ZAB cells is evaluated under various atmospheres: ambient air and humid conditions and temperatures. Notably, in a humid environment, the cells achieved extended cycling stability, operating for over 500 h—significantly longer than under open-air conditions. Overall, this study highlights the importance of tailored GPE design and efficient bifunctional catalysts to enhance the performance and longevity of zinc-air batteries for long-duration energy storage applications.

Catalyst↗

252 Cf yield calibration method for nuclear material accountancy and safeguards practitioners

Californium-252 is an isotope commonly encapsulated as a physically small but strong spontaneous fission neutron source for applications in industry, academia, and research. Within the nuclear safeguards community, a well-characterized 252 Cf source is often used as an accessible alternative for plutonium in calibrations measurements, which require the absolute source strength. Current methods of source strength quantification can provide an accurate estimate, approximately 1% uncertainty under optimal conditions, but are typically costly and time consuming. An alternative method was developed to determine 252 Cf source strength using passive neutron correlation counting (PNCC). The PNCC method enables institutions and facilities to perform 252 Cf source calibration measurements in-house using detection systems that are common within the nuclear safeguards community. This novel method was previously successfully demonstrated using neutron multiplicity well counters. However, the previous evaluation utilized detection systems with high neutron detection efficiencies, greater than 60%. The purpose of the current study is to extend the previous evaluation and demonstrate the feasibility of the PNCC 252 Cf calibration method for suite of coincidence counters with lower neutron detection efficiencies, between 15% and 35%, which are more commonly encountered in the field, as well as to provide a step-by-step guide to using the method. The neutron source used in this evaluation was previously certified by the National Institutes of Science and Technology (NIST), which provides a reference for the accuracy of the PNCC method. In conclusion, the present source yield calculations demonstrate excellent agreement with a NIST calibration technique and achieve a standard uncertainty below the target 1%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel–Ligand Docking

The identification of promising lead compounds showing pharmacological activities toward a biological target is essential in early stage drug discovery. With the recent increase in available small-molecule databases, virtual high-throughput screening using physics-based molecular docking has emerged as an essential tool in assisting fast and cost-efficient lead discovery and optimization. However, the best scored docking poses are often suboptimal, resulting in incorrect screening and chemical property calculation. We address the pose classification problem by leveraging data-driven machine learning approaches to identify correct docking poses from AutoDock Vina and Glide screens. To enable effective classification of docking poses, we present two convolutional neural network approaches: a three-dimensional convolutional neural network (3D-CNN) and an attention-based point cloud network (PCN) trained on the PDBbind refined set. We demonstrate the effectiveness of our proposed classifiers on multiple evaluation data sets including the standard PDBbind CASF-2016 benchmark data set and various compound libraries with structurally different protein targets including an ion channel data set extracted from Protein Data Bank (PDB) and an in-house KCa3.1 inhibitor data set. Our experiments show that excluding false positive docking poses using the proposed classifiers improves virtual high-throughput screening to identify novel molecules against each target protein compared to the initial screen based on the docking scores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Higher Ion Selectivity with Lower Energy Usage Promoted by Electro-osmotic Flow in the Transport through Conical Nanopores

The tradeoff between selectivity and throughput presents fundamental challenges to improve desalination and charge storage, salinity gradient-based energy harvesting, memory device/circuit development, and so forth. The well-known ion-current rectification and the recently resolved time-dependent transport hysteresis in conical nanopores or asymmetric nanointerfaces offer new opportunities for the selective transport of matter. This report shows that electro-osmotic flow (EOF) is an overlooked factor that increases ion selectivity while maintaining enhanced transport throughput in rectified nanoscale electrokinetic transport. The increased selectivity originates primarily from the suppression of anion flux by the fluid flow in the opposite direction under the applied electrical field. By solving the Poisson and Nernst–Planck (PNP) equations without and with coupled Navier–Stokes (PNP–NS) equations, the EOF effects on cation and anion transport are unequivocally revealed in asymmetric nanopipettes. The flux of cations and anions as well as the transference number and flow velocity are elucidated using the models and boundary conditions validated by previous experiments. A dimensionless parameter, radius over the Debye length, reveals optimal ion selectivity and energy cost at intermediate ion concentrations and nanopore sizes, up to hundreds of millimolars and tens of nanometers under time-dependent potential stimulus. Furthermore, the fundamental insights into EOF at nanointerfaces suggest new routes/strategies for better separation, analysis, and energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PbS/CdS Quantum Dot Room-Temperature Single-Emitter Spectroscopy Reaches the Telecom O and S Bands via an Engineered Stability

We synthesized PbS/CdS core/shell quantum dots (QDs) to have functional single-emitter properties for room-temperature, solid-state operation in the telecom O and S bands. Two shell-growth methods–cation exchange and successive ionic layer adsorption and reaction (SILAR)–were employed to prepare QD heterostructures with shells of 2–16 monolayers. PbS/CdS QDs were sufficiently bright and stable to resolve photoluminescence (PL) spectra representing both bands from single nanocrystals using standard detection methods, and for a QD emitting in the O-band a second-order correlation function showed strong photon antibunching, important steps toward demonstrating the utility of lead chalcogenide QDs as single-photon emitters (SPEs). Irrespective of type, few telecom-SPEs exist that are capable of such room-temperature operation. Access to single-QD spectra enabled a direct assessment of spectral line width, which was ~70–90 meV compared to much broader ensemble spectra (~300 meV). We show inhomogeneous broadening results from dispersity in PbS core sizes that increases dramatically with extended cation exchange. Quantum yields (QYs) are negatively impacted at thick shells (>6 monolayers) and, especially, by SILAR-growth conditions. Time-resolved PL measurements revealed that, with SILAR, initially single-exponential PL-decays transition to biexponential, with opening of nonradiative carrier-recombination channels. Radiative decay times are, overall, longer for core/shell QDs compared to PbS cores, which we demonstrate can be partially attributed to some core/shell sizes occupying a quasi-type II electron–hole localization regime. Finally, we demonstrate that shell engineering and the use of lower laser-excitation powers can afford significantly suppressed blinking and photobleaching. However, dependence on shell thickness comes at a cost of less-than-optimal brightness, with implications for both materials and experimental design

36 MATERIALS SCIENCE↗