Search NASA⌕ Search

SEARCH · Search NASA

Results for “Shape Optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,315 records · Page 73

Coordinated resource allocation to plant growth–defense tradeoffs

Summary Plant resource allocation patterns often reveal tradeoffs that favor growth (G) over defense (D), or vice versa. Ecologists most often explain G–D tradeoffs through principles of economic optimality, in which negative trait correlations are attributed to the reconciliation of fitness costs. Recently, researchers in molecular biology have developed ‘big data’ resources including multi‐omic (e.g. transcriptomic, proteomic and metabolomic) studies that describe the cellular processes controlling gene expression in model species. In this synthesis, we bridge ecological theory with discoveries in multi‐omics biology to better understand how selection has shaped the mechanisms of G–D tradeoffs. Multi‐omic studies reveal strategically coordinated patterns in resource allocation that are enabled by phytohormone crosstalk and transcriptional signal cascades. Coordinated resource allocation justifies the framework of optimality theory, while providing mechanistic insight into the feedbacks and control hubs that calibrate G–D tradeoff commitments. We use the existing literature to describe the coordinated resource allocation hypothesis (CoRAH) that accounts for balanced cellular controls during the expression of G–D tradeoffs, while sustaining stored resource pools to buffer the impacts of future stresses. The integrative mechanisms of the CoRAH unify the supply‐ and demand‐side perspectives of previous G–D tradeoff theories.

Monson, Russell K.↗

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Transonic analysis and design of axisymmetric bodies in nonuniform flow

An inviscid nonuniform axisymmetric transonic code was developed for applications in analysis and design. Propfan slipstream effect on pressure distribution for a body with and without sting was investigated. Results show that nonuniformity causes pressure coefficient to be more negative and shock strength to be stronger and more rearward. Sting attached to a body reduced the pressure peak and moves the rear shock forward. Extent and Mach profile shapes of the nonuniformity region appeared to have little effect on the pressure distribution. Increasing nonuniformity magnitude made pressure coefficient more negative and moved the shock rearward. Design study was conducted with the CONMIN optimizer for an ellipsoid and a body with the NACA-0012 counter. For the ellipsoid, the general trend showed that to reduce the pressure drag, the front portion of the body should be thinner and the contour of the rear portion should be flatter than the ellipsoid. For the design of a body with a sharp trailing edge in transonic flow with an initial shape given by the NACA-0012 contour, the pressure drag was reduced by decreasing the nose radius and increasing the thickness in the aft portion. Drag reduction percentages are given.

Chang, Jen-Fu↗

Aerodynamic Optimization of Mach 0.8 Transonic Truss-Braced Wing Aircraft using Variable Camber Continuous Trailing Edge Flap

This paper presents an aerodynamic optimization study of the Mach 0.8 Transonic Truss-Braced Wing (TTBW) aircraft with Variable Camber Continuous Trailing Edge Flap (VC-CTEF). The VCCTEF is a novel wing shaping control concept to improve aircraft aerodynamic efficiency. Drag reduction studies are conducted for two different VCCTEF configurations with 6- and 10-spanwise sections, respectively. A simple VCCTEF actuator weight model is used to account the weight penalty of the actuator in the design for the Mach 0.8 TTBW aircraft. A vortex-lattice model of the Mach 0.8 TTBW aircraft is developed with transonic small disturbance, integral boundary-layer, and wing-strut interference corrections for rapid aerodynamic performance evaluations. The VSPAERO model has been validated against the wind tunnel test data. The optimization results show that the 6-spanwise sections VCCTEF provides a relatively better solution for drag reduction when the actuator weight penalty is considered. A high-fidelity CFD solver FUN3D is used to verify the VCCTEF optimization design.

Aerodynamic optimization↗

The transition from resistance to acceptance: Managing a marine invasive species in a changing world

Abstract Marine invasive species can transform coastal ecosystems, yet mitigating their effects can be difficult, and even impractical. Often, marine invasive species are managed at poorly matched spatial scales, and at the same time, rates of spread and establishment are increasing under climate change and can outpace resources available for population suppression. These circumstances challenge traditional conservation goals of maintaining a historic environmental state, especially for a species like the European green crab ( Carcinus maenas ), a formidable invader with few examples of successful long‐term removal programs. A management paradigm where decision alternatives include resisting or accepting a new ecological trajectory may be needed. We apply mathematical concepts from decision theory to develop a quantitative framework for navigating management decisions in this new resist‐accept paradigm. We develop a model of European green crab growth, removal and colonization, and we find optimal levels of removal effort that minimize both ecological change and removal cost. We establish a benchmark of colonization pressure at which green crab density becomes decoupled from a decision maker's actions, such that population control can no longer shape the invasion trajectory. For informing the decision boundary between resistance and acceptance, our results highlight that a decision maker's understanding of how removal cost scales with removal effort is more important than understanding the density‐impact relationship. We show that assuming stationary system dynamics can result in sub‐optimal levels of species removal effort, highlighting the importance of developing anticipatory management strategies by accounting for non‐stationary dynamics. Policy implications . For marine invasive species that can disperse across long distances and recolonize rapidly after removal, the focus of conservation policy should shift away from understanding how to resist change to understanding when to stop resisting change. Navigating this decision problem involves trade‐offs among competing objectives, highlighting the need for structured approaches to elicit objective weights that reflect the values of the decision maker. For natural resource managers facing possible ecosystem transformation, this decision framework can enable proactive and strategic decisions made under uncertainty in a changing world.

Keller, Abigail G. [Department of Environment Scie↗

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) can not fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, the modeling error PDF by the tradional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. Furthermore, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.

Modelling↗

Beam Shaping and Oscillation for Metals Additive Manufacturing

Additive Manufacturing (AM) is pivotal for next-generation industrial manufacturing but is hampered by process control challenges leading to unwanted defects and sub-optimal material properties. Our research builds on prior work that utilized beam oscillation techniques to mitigate these issues (Wu et al., 2023). We focus on investigating the influence of beam oscillation frequency on melt pool dynamics, utilizing in-situ synchrotron material characterization from the ESRF (Chen et al., 2026). Preliminary findings indicated that beam oscillation results in unique fluid flow patterns and enhanced melting stability. These findings suggested the possibility of optimized AM process control, including minimized defects and tailored thermal histories. We proposed further research to explore the effects of beam oscillation frequencies comprehensively, using the in-situ characterization capabilities at the ESRF. The goal was to quantify this relationship, offering a pathway to more precise AM process control and optimization. Our research is expected to offer new scientific insights into the fluid mechanics and thermal behaviour in AM, contributing to its broader applicability and commercial viability.

36 MATERIALS SCIENCE↗

Optimal discrete-time dynamic output-feedback design - A w-domain approach

An alternative method for optimal digital control design is described in this paper. The method is based on the usage of the w-transform and has many attractive design features. One of these is its immediate connection with frequency loop-shaping techniques that are now popular and effective for multivariable control synthesis in continuous-time domain. Furthermore, any design algorithms originally developed for continuous-time systems can now be immediately extended to the discrete-time domain. The main results presented in this paper are the exact problem formulation and solution of an optimal discrete-time dynamic output-feedback design in the w-domain involving a quadratic performance index to random disturbances. In addition, necessary conditions for optimality are obtained for the numerical solution of the optimal output-feedback compensator design. A numerical example is presented illustrating its application to the design of a low-order dynamic compensator in a stability augmentation system of a commercial transport.

Ha, Cheolkeun↗

Modeling and Optimization for Morphing Wing Concept Generation II: Morphing Wing Modeling and Structural Sizing Techniques - Part 1

This report documents a series of investigations to develop an approach for structural sizing of various morphing wing concepts. For the purposes of this report, a morphing wing is one whose planform can make significant shape changes in flight - increasing wing area by 50% or more from the lowest possible area, changing sweep 30 or more, and / or increasing aspect ratio by as much as 200% from the lowest possible value. These significant changes in geometry mean that the underlying load-bearing structure changes geometry. While most finite element analysis packages provide some sort of structural optimization capability, these codes are not amenable to making significant changes in the stiffness matrix to reflect the large morphing wing planform changes. The investigations presented here use a finite element code capable of aeroelastic analysis in three different optimization approaches -a "simultaneous analysis" approach, a "sequential" approach, and an "aggregate" approach.

Skillen, Michael D.↗

Aerodynamic Optimization of Mach 0.745 Transonic Truss-Braced Wing Aircraft with Variable-Camber Continuous Trailing-Edge Flap

This paper presents an aerodynamic optimization study of the Mach 0.745 Transonic Truss-Braced Wing (TTBW) aircraft with Variable-Camber Continuous Trailing-Edge Flap (VC-CTEF). The VCCTEF is a novel wing shaping control concept to improve aircraft aerodynamic efficiency. Drag reduction studies are conducted for three different VCCTEF configurations with 6-, 10-, and 21-spanwise sections, respectively. A simple VCCTEF actuator weight model is proposed to account the weight penalty of the actuator in the design. A vortex-lattice model of the TTBW model is developed with transonic small disturbance, integral boundary-layer, and wing-strut interference corrections for rapid aerodynamic performance evaluations. The VSPAERO model has been validated against wind tunnel test data. The optimization results show that the 21-spanwise sections VCCTEF has largest absolute drag coefficient reduction, however, the 6-spanwise sections VCCTEF provides a relatively better solution for drag reduction when the actuator weight penalty is considered. A high-fidelity CFD solver FUN3D is used to validate the VCCTEF optimization.

Aerodynamic Optimization↗

CONCEPT OF A POLARIZED POSITRON SOURCE FOR CEBAF

Positron beams would provide new and meaningful probes for the experimental program at the Thomas Jefferson National Accelerator Facility (JLab), including but not limited to future hadronic physics and dark matter experiments. Critical requirements involve generating positron beams with a high degree of spin polarization, sufficient intensity and a continuous-wave (CW) bunch train compatible with acceleration to 12 GeV at the Continuous Electron Beam Accelerator Facility (CEBAF). To address these requirements, a polarized positron injector based upon the bremsstrahlung of an intense CW spin polarized electron beam is considered*. First a polarized electron beam line provides >1 mA of polarized electrons at ~120 MeV to a high-power target for positron production. Next, a second beam line collects, shapes and aligns the spin of positrons for users. Finally, the positron beam is matched into the CEBAF acceptance for acceleration and transport to the end stations with energies up to 12 GeV. An optimized layout to provide positrons beams with intensity >100 nA (polarized) or intensity >3 µA (unpolarized) will be discussed in this poster.

Habet, S. H.↗

Optimum Multinozzle Configuration for Minimizing the Rayleigh Integral During High-Frequency Transverse Instabilities

This paper develops a formalism for optimizing nozzle location/configuration with respect to combustion stability of high-frequency transverse modes in a can combustor. The stability of these acoustically noncompact flames was assessed using the Rayleigh integral (RI). Several key control parameters influence RI—flame angle, swirling strength, nozzle location, as well as nozzle location with respect to the acoustic mode shape. In this study, we consider a N-around-1 configuration such as typically used in a multi-nozzle can system and study the overall stability of this system for different natural transverse modes. Typically, such nozzles are distributed in a uniformly circular manner for which we study the overall RI, and for cases where RI > 0, we optimize the nozzle distribution that can reduce and minimize RI. For a fixed geometry such as a circular configuration, the analysis shows how the flame's parameters must vary across the different nozzles, to result in a relatively stable system. Additionally, for a fixed set of flame parameters, the analysis also indicates the noncircular distribution of the N nozzles that minimizes RI. Overall, the analysis aims to provide insights on designing nozzle locations around the center nozzle for minimal amplification of a given transverse mode.

42 ENGINEERING↗

Analytical Approach for Detection of Ergosterol in Mushrooms Based on Modification Free Electrochemical Sensor in Organic Solvents

Ergosterol (Erg) is the major sterol component in the plasma membranes of fungi. The main goal of this work was to develop rapid, reliable, and cost-effective method toward Erg detection based on application of unmodified boron-doped diamond electrode. Several organic solvents were tested (acetonitrile, dimethyformamide, dimethylsulfoxide, dichloromethane), and it was found that best analytical characteristics were achieved using acetonitrile containing 0.1 M tetrabutylammonium hexa-fluorophosphate as supporting electrolyte. Oval shaped and well-defined oxidation peak was recorded at potential of around 1.17 V versus Ag/Ag+ non-aqueous reference electrode. Under optimized experimental conditions, linear working range from 2 to 200 mu M was estimated, with limit of detection of 0.7 mu M, using square wave voltammetry. Negligible effect of possible interfering compound was observed. Proposed methodology was successfully applied for estimation of Erg content in mushrooms extract with satisfactory results in comparison with spectrophotometric procedure. Obtained results clearly show that developed analytical methodology can be adequate replacement for the, up to date, used methods and open-novel approach for ergosterol detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designing robust energy policy packages under deep uncertainty: A multi-metric decision support framework

The complexity of transitioning to sustainable energy systems requires policy frameworks capable of balancing multiple objectives while addressing deep uncertainty. However, existing approaches often lack systematic methods to identify combinations of policy levers that remain effective across a wide range of uncertain futures. This paper presents a novel decision support framework that guides the selection of robust policy packages based on their performance across multiple objectives under uncertainty. Our method leverages a large ensemble of scenarios and applies scenario discovery techniques to identify influential policy levers. Here, we introduce new indicators to assess the robustness of policies by evaluating their ability to mitigate adverse outcomes across metrics. These indicators support an iterative process to build a robust policy package. Finally, we map the technological and energy pathways associated with the robust policy package by leveraging an energy system optimization model. We illustrate the application of this framework to the Spanish energy system, providing insights into how specific combinations of policy levers shape decarbonization pathways under uncertainty.

Decision-support method↗

Microbe of the month: Methanococcus maripaludis

Methanococcus maripaludis was first isolated in 1983 from the anoxic sediment of a salt marsh in South Carolina, USA. M. maripaludis grows by using H 2 or formate to reduce CO 2 to CH 4 and is an autotroph that assimilates CO 2 via the archaeal version of the Wood–Ljungdahl pathway. In some strains, supplementation of growth medium with acetate or propionate can increase biomass yield. Furthermore, this microorganism is strictly anaerobic, has a pleomorphic coccoid shape, and forms translucent, pale yellow, smooth colonies within 3 days on agar plates. The optimum temperature for growth is 38°C with optimal pH between 6.8 and 7.2.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular Lignin Solubility and Structure in Organic Solvents

Lignin, a polymer found in the secondary plant cell wall of terrestrial plants, is the single largest source of renewable aromatics and has attracted considerable attention as a feedstock for potential industrial use. However, the secondary plant cell wall is a crowded environment, and lignin in its native form interacts with other biomass components within a larger network. Application of some organic solvents is known to liberate lignin from this network and creates lignin-rich streams suitable for conversion into target products. Through molecular-scale lignin simulation, we analyze how diverse lignin polymers change their structure in response to varying organic solvent environments. We quantify the relationship between solvent polarity and lignin polymer extension, observing maximum polymer expansion and solvation for solvents with polarity near those of dimethyl sulfoxide. From our observations at the nanoscale, increasing syringyl content within lignin polymers reduces the expansion of the polymer in organic solvent environments and decreases the free energy difference compared to aqueous solvent environments, thereby reducing solubility for high syringyl lignin polymers. The conformational transition rates between lignin polymer shapes increased through a combination of the solvent diffusion constant and polymer extension. The molecular simulations indicate that there is likely no single optimal organic solvent for lignin. Different solvent mixtures have optimal or near-optimal properties in solubilizing lignin polymers, thereby disrupting interactions with other biopolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of protein-binding proteins from the target structure alone

The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains a challenge. Here we describe a general solution to this problem that starts with a broad exploration of the vast space of possible binding modes to a selected region of a protein surface, and then intensifies the search in the vicinity of the most promising binding modes. We demonstrate the broad applicability of this approach through the de novo design of binding proteins to 12 diverse protein targets with different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and, following experimental optimization, bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of five of the binder–target complexes, and all five closely match the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein–protein interactions, and should guide improvements of both. Our approach enables the targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of tensile loading during annealing of alnico melt spun ribbons

Conventional magnetic annealing (MA) of the permanent magnet alloy alnico involves application of an external magnetic field at temperatures within the spinodal decomposition range. This field biases the growth of the Fe-Co rich, ferromagnetic α 1 -phase in an energetically favorable 〈001〉 direction in alignment with the applied field within an Al-Ni rich, paramagnetic α 2 -phase. Utilizing a magnetic field to bias the α 1 -phase may limit alnico from reaching theoretical coercivity due to (1) the field having maximum biasing ability at temperatures near the Curie temperature where large α 1 -phase nanorods form and (2) connectivity of the α 1 -phase occurs unavoidably during MA. Both decrease the effective shape anisotropy of the α 1 -phase, thereby reducing coercivity. Herein, we explore tensile-loading as a biasing mechanism to control and optimize the final alnico nanostructure beyond that achieved by MA. Two samples of melt-spun alnico were heat-treated at 860 °C for 5 minutes: one sample was subjected to 10 MPa tensile stress for comparison with a stress-free control sample. Structural and magnetic characterization revealed that the stress-annealed ribbon sample possessed expected phase assemblages, but was distinguished by a ∼2× larger grain diameter and an elongated anisotropic α 1 -phase within grains that were oriented to a shear stress along 〈001〉 directions at an angle of ∼45° relative to the loading direction. Both types of annealing produced a similar increase in the coercivity and remanence, but a decrease in saturation magnetization.

Rinko, E. A.↗