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The design, fabrication, and subsequent testing of four power slip rings for synchronous orbit application are described. The synergistic effects of contact materials and slip ring-brush design are studied by means of frequent and simultaneous recording of friction, wear, and electrical noise. Data generated during the test period are presented along with post test analysis data.
There is a strong need for developing multifunctional materials to reduce the cost of applied material without compromising the performance of the detectors, devices and sensors. The materials design, processing, growth and fabrication of bulk and nanocrystals and fabrication into devices and sensors involve huge cost and resources including a multidisciplinary team of experts. Because of this reason, prediction of multifunctionality of materials before design and development should be evaluated. Chalcogenides and chalcopyrites are a very exciting class of materials for developing multifunctionality. Materials such as Gallium selenide GaSe and zinc selenide ZnSe have been proven to be excellent examples. GaSe is a layered material and very difficult to grow in large crystal. However, it's ternary and quaternary analogs such as thallium gallium selenide TlGaSe2, thallium gallium selenide sulfide TlGaSe2-xSs, thallium arsenic selenide Tl3AsSe3, silver gallium selenide AgGaGe3Se8, AgGaGe5Se12 and several others have shown great promise for multifunctionality. Several of these materials have shown good efficiency for frequency conversion (nonlinear optical NLO), electro-optic modulation, and acousto-optic tunable filters and imagers suitable for the visible, near-infrared wavelength, mid wave infrared (MWIR), long wave infrared (LWIR) and even up to Tera hertz wavelength (THW) regions. In addition, this class of materials have demonstrated low absorption coefficients and power handling capability in the systems. Also, these crystals do not require post growth annealing, show very large transparency range and fabricability.
The design, fabrication, and testing of four power slip rings for synchronous orbit application are considered. Environmental and instrumentation systems necessary for monitoring electrical noise, friction, and brush wear in air and at less than 5 X 10 to the minus 8th power torr were developed. Composite brushes consisting of silver-molybdenum disulfide-graphite and silver-niobium diselenide-graphite were employed on rings of coin silver and rhodium plate. These four contact combinations were tested during ambient condition run-in at 150 and a humidity sequence at 0.1. The first nine months of a two year vacuum test performed at 0.1 rpm were completed.
The organization of a proposed ceramic structural materials program is described, and a suggested course sequence for college-level and graduate-level courses is presented. The course work on ceramics and brittle fracture are intended to lead to a brittle material design project and a brittle material design problem. Criteria for the selection of appropriate projects/problems are considered.
Designing fiber-reinforced polymer composites (FRPCs) with a tailored nonlinear stress-strain response is crucial for applications such as energy absorption in crash structures, flexible robotics, and impact-resistant protective gear. However, the inherent complexities of composite materials and the multitude of parameters involved, render traditional design and optimization methods inadequate for achieving effective inverse design of composites. In this paper, we present an AI-based inverse design framework that effectively and efficiently generates FRPCs with targeted nonlinear stress-strain responses. We introduce a physically constrained diffusion model (PC3D_Diffusion) capable of managing the complexities of composite materials and producing detailed, high-quality designs. We propose a loss-guided, learning-free approach to generate physically feasible microstructure designs by explicitly enforcing physical constraints during the generation process. For training purposes, 1.35 million FRPC samples were created, and their corresponding stress-strain curves were computed using established physics-based computational models. The results show that PC3D_Diffusion consistently generates high-quality designs with tailored mechanical behaviors, while guaranteeing compliance with the physical constraints. PC3D_Diffusion advances FRPC inverse design and may facilitate the inverse design of other 3D materials, offering potential applications in industries reliant on materials with custom mechanical properties.
Machine learning models that establish the relationships between materials processing and properties can enable inverse design of materials through active learning. Alchemite is a commercial software that can perform inverse materials design on sparse data. Here we evaluate Alchemite’s performance on a dataset of shape memory alloys and a dataset of heat exchangers compared to baseline random forest models. Alchemite had higher accuracy when making predictions on sparse data and was more accurate or nearly as accurate as random forests on complete datasets while also quantifying uncertainty. The software was also used to suggest processing steps and design parameters to optimize properties and performance; however, physical validation of the suggested design parameters was beyond the scope of this work. Several useful design insights were gained about the impact of the design parameters on properties and performance including the importance of dopant choice and amount for shape memory alloys and the importance of height and weight on the thermal resistance of heat exchangers.
NASA's projects and missions push the bounds of what is possible. To support the agency's work, materials development must stay on the cutting edge in order to keep pace. Today, researchers at NASA Ames Research Center perform multiscale modeling to aid the development of new materials and provide insight into existing ones. Multiscale modeling enables researchers to determine micro- and macroscale properties by connecting computational methods ranging from the atomic level (density functional theory, molecular dynamics) to the macroscale (finite element method). The output of one level is passed on as input to the next level, creating a powerful predictive model.
Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.
New designs, and materials appropriate for such designs, are under investigation in an effort to develop coronagraph occulting masks having broad-band spectral characteristics superior to those currently employed. These designs and materials are applicable to all coronagraphs, both ground-based and spaceborne. This effort also offers potential benefits for the development of other optical masks and filters that are required (1) for precisely tailored spatial transmission profiles, (2) to be characterized by optical-density neutrality and phase neutrality (that is, to be characterized by constant optical density and constant phase over broad wavelength ranges), and/or (3) not to exhibit optical- density-dependent phase shifts. The need for this effort arises for the following reasons: Coronagraph occulting masks are required to impose, on beams of light transmitted through them, extremely precise control of amplitude and phase according to carefully designed transmission profiles. In the original application that gave rise to this effort, the concern has been to develop broad-band occulting masks for NASA s Terrestrial Planet Finder coronagraph. Until now, experimental samples of these masks have been made from high-energy-beam-sensitive (HEBS) glass, which becomes locally dark where irradiated with a high-energy electron beam, the amount of darkening depending on the electron-beam energy and dose. Precise mask profiles have been written on HEBS glass blanks by use of electron beams, and the masks have performed satisfactorily in monochromatic light. However, the optical-density and phase profiles of the HEBS masks vary significantly with wavelength; consequently, the HEBS masks perform unsatisfactorily in broad-band light. The key properties of materials to be used in coronagraph occulting masks are their extinction coefficients, their indices of refraction, and the variations of these parameters with wavelength. The effort thus far has included theoretical predictions of performances of masks that would be made from alternative materials chosen because the wavelength dependences of their extinction coefficients and their indices of refraction are such that that the optical-density and phase profiles of masks made from these materials can be expected to vary much less with wavelength than do those of masks made from HEBS glass. The alternative materials considered thus far include some elemental metals such as Pt and Ni, metal alloys such as Inconel, metal nitrides such as TiN, and dielectrics such as SiO2. A mask as now envisioned would include thin metal and dielectric films having stepped or smoothly varying thicknesses (see figure). The thicknesses would be chosen, taking account of the indices of refraction and extinction coefficients, to obtain an acceptably close approximation of the desired spatial transmittance profile with a flat phase profile
Fouling of surfaces introduces significant operational and economic challenges in marine and membrane systems. While empirical fouling assays and surface science methodologies have independently introduced fouling resistant methodologies and functionalities within each of these respective application spaces, they remain limited by their inability to extrapolate findings across length scales and inform materials design strategies. This perspective emphasizes the need to bridge the macroscale fouling assays conducted in the marine community and molecular-scale insights obtained from the membranes community. Here, by uniting these approaches, generalized design strategies can be developed across applications, leading to the realization of effective antifouling materials over a wide spectrum of operating conditions and foulant types. Standardized and high-throughput methodologies are proposed as tools to unify research efforts to drive the development of next-generation antifouling coatings and treatments.
Bearings for vacuum operation retainer material and design
Computational design for fission reactor materials is ready to accelerate the development and qualification of nuclear materials. This review is primarily aimed at computational materials scientists that seek to apply ICME to the development of fission reactor materials. We summarize reactor materials and technology, discuss reactor material development and qualification today, show how ICME is being applied to the unique requirements of reactor materials, and provide a future vision.
Potential structural materials and design considerations for helicopters and light general aircraft
Potential structural materials and design concepts for light aircraft
Design synthesis relationship derived for primary structural weight of membrane type pressure vessels of anisotropic materials
Using piezoceramic materials is one way the design engineer can create structures which have an ability to both sense and respond to their environment. Piezoceramic materials can be used to create structural sensors and structural actuators. Because piezoceramic materials have transduction as a material property, their sensing or actuation functions are a result of what happens to the material. This is different than discrete devices we might attach to the structure. For example, attaching an accelerometer to a structure will yield an electrical signal proportional to the acceleration at the attachment point on the structure. Using a electromagnetic shaker as an actuator will create an applied force at the attachment point. Active material elements in a structural design are not easily modeled as providing transduction at a point, but rather they change the physics of the structure in the areas where they are used. Hence, a designer must not think of adding discrete devices to a structure to obtain an effect, but rather must design a structural system which accounts for the physical principles of all the elements in the structure. The purpose of this manual is to provide practicing engineers the information necessary to incorporate piezoelectric materials in structural design and machine design. First, we will review the solid-state physics of piezoelectric materials. Then we will discuss the physical characteristics of the electrical-active material-structural system. We will present the elements of this system which must be considered as part of the design task for a structural engineer. We will cover simple modeling techniques and review the features and capabilities of commercial design tools that are available. We will then cover practical how-to elements of working with piezoceramic materials. We will review sources of piezoceramic materials and built-up devices, and their characteristics. Finally, we will provide two design examples using piezoceramic materials, first as discrete actuators for vibration isolation, and second as structurally-distributed sensor/actuators for active acoustic control.
The goal of the ablation technology program is to bring ablation research and development to a high state of readiness for application to space shuttle vehicles. Some recent results and current work in the areas of materials, designs, and refurbishment for ablative TPS are reported. Future research and development needs are also presented.
Potential structural materials and design concepts evaluated for light aircraft applications