Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Method of Manufactured Solutions”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Additive manufacturing for electrocaloric terpolymer thin films

Current heating, venting, and air conditioning (HVAC) systems have drawbacks of high energy consumption, large CO 2 emissions, and low efficiency. Electrocaloric (EC) cycles present an eco-friendly alternative by converting thermal energy to electrical energy. Defect-free thin films with uniform thickness are required to achieve optimal EC performance. A scalable thin film fabrication process is essential for integrating EC cycles into HVAC systems. This study introduces EC thin films prepared by electrospray (ES) processing, a manufacturing method that deposits EC polymer layer by layer using high voltage. The resulting films show superior thickness control, smoother surfaces, and improved thermal and electrical properties compared with solution casting. In addition, post-annealing at 120°C enhances the thermal and EC performance, with films achieving a temperature change (ΔT) of 3.6°C at 100 MV/m when tested near room temperature. With the potential for future scalability, the ES method offers a promising approach for fabricating EC thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scalable Deep Learning-Based Microarchitecture Simulation on GPUs

Cycle-accurate microarchitecture simulators are essential tools for designers to architect, estimate, optimize, and manufacture new processors that meet specific design expectations. However, conventional simulators based on discrete-event methods often require an exceedingly long time-to-solution for the simulation of applications and architectures at full complexity and scale. Given the excitement around wielding the machine learning (ML) hammer to tackle various architecture problems, there have been attempts to employ ML to perform architecture simulations, such as Ithemal and SimNet. However, the direct application of existing ML approaches to architecture simulation may be even slower due to overwhelming memory traffic and stringent sequential computation logic. This work proposes the first graphics processing unit (GPU)-based microarchitecture simulator that fully unleashes the potential of GPUs to accelerate state-of-the-art ML-based simulators. First, considering the application traces are loaded from central processing unit (CPU) to GPU for simulation, we introduce various designs to reduce the data movement cost between CPUs and GPUs. Second, we propose a parallel simulation paradigm that partitions the application trace into sub-traces to simulate them in parallel with rigorous error analysis and effective error correction mechanisms. Combined, this scalable GPU-based simulator outperforms by orders of magnitude the traditional CPU-based simulators and the state-of-the-art ML-based simulators, i.e., SimNet and Ithemal.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Comparison of the Mechanical Properties of a Conjugated Polymer Deposited Using Spin Coating, Interfacial Spreading, Solution Shearing, and Spray Coating

The mechanical properties of π-conjugated (semiconducting) polymers are a key determinant of the stability and manufacturability of devices envisioned for applications in energy and healthcare. These properties—including modulus, extensibility, toughness, and strength—are influenced by the morphology of the solid film, which depends on the method of processing. To date, the majority of work done on the mechanical properties of semiconducting polymers has been performed on films deposited by spin coating, a process not amenable to the manufacturing of large-area films. Here, we compare the mechanical properties of thin films of regioregular poly(3-heptylthiophene) (P3HpT) produced by three scalable deposition processes—interfacial spreading, solution shearing, and spray coating—and spin coating (as a reference). Our results lead to four principal conclusions. (1) Spray-coated films have poor mechanical robustness due to defects and inhomogeneous thickness. (2) Sheared films show the highest modulus, strength, and toughness, likely resulting from a decrease in free volume. (3) Interfacially spread films show a lower modulus but greater fracture strain than spin-coated films. (4) The trends observed in the tensile behavior of films cast using different deposition processes held true for both P3HpT and poly(3-butylthiophene) (P3BT), an analogue with a higher glass transition temperature. Grazing incidence X-ray diffraction and ultraviolet–visible spectroscopy reveal many notable differences in the solid structures of P3HpT films generated by all four processes. Herein, while these morphological differences provide possible explanations for differences in the electronic properties (hole mobility), we find that the mechanical properties of the film are dominated by the free volume and surface topography. In field-effect transistors, spread films had mobilities more than 1 magnitude greater than any other films, likely due to a relatively high proportion of edge-on texturing and long coherence length in the crystalline domains. Overall, spread films offer the best combination of deformability and charge-transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scalable Synthesis of Pt/SrTiO 3 Hydrogenolysis Catalysts in Pursuit of Manufacturing-Relevant Waste Plastic Solutions

Here, an improved hydrothermal synthesis for shape-controlled, size-controlled 60 nm SrTiO 3 nanocuboid (STO NC) supports, which facilitates the scalable creation of platinum nanoparticles catalyst supported on STO (Pt/STO) for the chemical conversion of waste polyolefins, is reported herein. This synthetic method: 1) produces STO NC supports with average sizes ranging from 25 – 80 nm with narrow size distributions 2) demonstrates how SrCO 3 formation and variation in solution pH prevent the formation of STO NCs, and 3) establishes that STO nucleation prior to the hydrothermal treatment favors nanocuboid formation. The updated hydrothermal synthesis was scaled-up and conducted in a 4L batch reactor, resulting in STO NCs of comparable size and morphology (m = 22.5 g, d avg = 58.6 ± 16.2 nm) to those synthesized under standard hydrothermal conditions in a lab-scale 125 mL autoclave reactor. Size-controlled STO NCs, ranging in roughly 10 nm increments from the 25 nm to 80 nm, were used to support Pt deposited through strong electrostatic adsorption (SEA), a practical and scalable solution-based method. Using SEA techniques and a STO support with an average size of 39.3 ± 6.3 nm, a Pt/STO catalyst with 3.6 wt% Pt was produced and used for high-density polyethylene hydrogenolysis under previously-reported conditions (170 psi H 2 , 300°C, 96h; final product: M w = 2400, Ð = 1.03). As a well-established model system for studying the behavior of heterogeneous catalysts and their supports in reactions, the Pt/STO system detailed in this work presents a unique opportunity to simultaneously convert waste plastic into commercially-viable products while gaining fundamental insight into the mechanism of polyethylene hydrogenolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A time-parallel method for scalable heat transfer simulations of additive manufacturing

Here, a major challenge in simulating the thermal behavior in additive manufacturing processes is the disparate length and time scales between transport phenomena occurring in the melt pool and the component. A common simulation approach relies on spatial decomposition for parallel computing, but due to the nature of heat transfer in AM, where most of the computational expenditure is localized near the melt pool, the computational speedup from spatial parallelization saturates quickly. Therefore, additional parallelism by means of time-domain decomposition is needed to fully take advantage of high-performance computing (HPC) resources. This work introduces a time-parallel method to improve the computational scalability of additive manufacturing simulations on HPC systems, while maintaining high temporal resolution of heat transfer near the melt pool. The method, inspired by the nonlinear paraexp formalism, performs an iterative superposition of nonlinear solutions to the initial value problem, integrating the heat equation across overlapping time-parallel intervals. For a single layer of the NIST AMB2018–01 L7 benchmark problem, the method achieves a 38.51x speedup in wall-clock time with a maximum error in the global temperature solution of 0.99%. This reduces the total solution time from 196.72 min to 5.11 min on 128 nodes of the ORNL Frontier supercomputer. The tradeoff between accuracy and total wall-clock time is investigated and recommendations for time-parallel deployment for AM problems are made.

Additive manufacturing↗
DOE OSTI2022

Scalability Testing Approach for Internet of Things for Manufacturing SQL and NoSQL Database Latency and Throughput

The proliferation of low-cost sensors and industrial data solutions has continued to push the frontier of manufacturing technology. Machine learning and other advanced statistical techniques stand to provide tremendous advantages in production capabilities, optimization, monitoring, and efficiency. The tremendous volume of data gathered continues to grow, and the methods for storing the data are critical underpinnings for advancing manufacturing technology. This work aims to investigate the ramifications and design tradeoffs within a decoupled architecture of two prominent database management systems (DBMS): sql and NoSQL. A representative comparison is carried out with Amazon Web Services (AWS) DynamoDB and AWS Aurora MySQL. The technologies and accompanying design constraints are investigated, and a side-by-side comparison is carried out through high-fidelity industrial data simulated load tests using metrics from a major US manufacturer. The results support the use of simulated client load testing for comparing the latency of database management systems as a system scales up from the prototype stage into production. As a result of complex query support, MySQL is favored for higher-order insights, while NoSQL can reduce system latency for known access patterns at the expense of integrated query flexibility. Here, by reviewing this work, a manufacturer can observe that the use of high-fidelity load testing can reveal tradeoffs in IoTfM write/ingestion performance in terms of latency that are not observable through prototype-scale testing of commercially available cloud DB solutions.

AWS↗
DOE OSTI2026

Compositional Homogeneity in Rapidly Solidified 316L stainless steel produced by laser powder-bed fusion processing

The segregation of alloying elements in rapidly solidified 316L stainless steel produced using additive manufacturing technologies is widely reported throughout literature. The microstructure of thin walls manufactured from 316L stainless steel using laser powder bed fusion are examined for the presence of alloy segregation, i.e. the rejection of solutes to grain boundaries. Metallographic methods including mechanical polishing and chemical etching are used to prepare samples for microanalysis m

Jankowski, Alan F. [Sandia National Laboratories (↗
DOE OSTI2024

Challenges in Tracking Waste Reduction Performance Improvement in Manufacturing Plants

The recently released Circularity Gap Report 2023 by Circle Economy Foundation found that the circularity score for the global economy is declining. This indicates that material extraction from virgin sources is climbing over earlier years. As per data released by US Geological Survey, material use in the US economy has increased exponentially with the expanding US economy over last century. EPA tracked municipal solid waste from 1960 to 2018 and found that 50% of the waste is destined for landfills. EPA estimates that US industry is responsible for 2.7 billion ton of solid non-hazardous waste annually in our mostly linear economy model. The circular economy framework aims at decoupling economic value generation from virgin materials extraction from nature. The linear model of material extraction and disposal at end of life is highly unsustainable. Manufacturing companies have realized this and in their commitments to sustainability are adopting ambitious waste reduction targets. Through Better Plants program US Department of Energy has established Waste Reduction Network where it is offering technical assistance to partners to achieve these ambitious waste reduction goals. Basic requirements of establishing a target include identifying a baseline, quantifying waste performance, and measuring progress over time. One problem faced by industry is the unstandardized metrics to quantify waste performance that may not be well suited to demonstrate progress. In this paper, we research methods traditionally used to measure waste performance and highlight advantages, gaps and limitations of each method. Suitability of the methods applicable to different manufacturing circumstances are also examined. Finally, we present a case study of a large manufacturer that faced inconsistencies in their tracked measurement metric. A solution was proposed to alter the methodology to enable more accurate waste performance tracking against a baseline.

Chaudhari, Subodh↗
DOE OSTI2024

An asymptotic-preserving semi-Lagrangian algorithm for the anisotropic heat transport equation with arbitrary magnetic fields

Here, we extend the recently proposed semi-Lagrangian algorithm for the extremely anisotropic heat transport equation [Chacón et al., J. Comput. Phys ., 272 (2014)] to deal with arbitrary magnetic field topologies. The original scheme (which showed remarkable numerical properties) was valid for the so-called tokamak-ordering regime, in which the magnetic field magnitude was not allowed to vary much along field lines. The proposed extension maintains the attractive features of the original scheme (including the analytical Green's function, which is critical for tractability) with minor modifications, while allowing for completely general magnetic fields. The accuracy and generality of the approach are demonstrated by numerical experiment with an analytical manufactured solution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Bench Scale Testing of Next Generation Hollow Fiber Membrane Modules

This project seeks to develop a next generation membrane material (PI-2) for application in Air Liquide’s (AL) hybrid process. Combining the cold membrane operation with an integrated CO 2 Compression and Purification Unit (CPU) significantly reduces the overall cost of CO 2 capture. The proposed work will accelerate the membrane bundle fabrication, scale-up and performance validation of this new material. The proposed novel membrane development, combined with the results of the previous Cold Membrane Project, will provide the best opportunity for AL to meet the long term development targets of the DOE with respect to timing, cost, and performance for CO 2 capture. Our previous field test program (DE-FE0013163) showed promising results for the hybrid process utilizing the existing commercial AL membrane bundles (PI-1 material). The project work has also shown the potential for significant improvements through initial laboratory tests with the novel material (PI-2). The initial PI-2 results show a step-change in membrane permeance. This will enable further reduction in the cost of CO 2 capture by reducing the number of membrane modules and associated equipment in the system. In order to capture this value, however, the new material needs to be validated by field testing of large bundles, representative of commercial production. Lastly, a comprehensive evaluation of novel hybrid processes and costs needs to be completed to ensure optimal use of this improved material performance. The current project seeks to develop this next generation membrane to TRL 5 (approximately 600 - 1,000 Nm3/h flue gas, 350 - 600 scfm, 0.2 - 0.3 MWe equivalent). Air Liquide manufacturing methodology will be applied to fabricate prototype (4”) membrane modules from PI-2 material. Once the manufacturing methods prove reliable with the new material, and performance is demonstrated in line with expectation, 6” commercial scale bundles will be fabricated. Recognizing that a low cost membrane solution by itself may not meet DOE’s LCOE target for CO 2 capture, we will also perform simulation studies of novel hybrid processes in combination with the next generation membrane technology. This approach has the best potential for exceeding the DOE targets. The best evaluation of the new commercial units will be performance testing under real flue gas at the NCCC. Finally, a rigorous TEA, which incorporates the novel process studies and field performance, will be completed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and reliability improvement of ML models empowered by UQ has the potential to significantly facilitate the broad adoption of ML solutions in high-stakes decision settings, such as healthcare, manufacturing, and aviation, to name a few. In this tutorial, we aim to provide a holistic lens on emerging UQ methods for ML models with a particular focus on neural networks and the applications of these UQ methods in tackling engineering design as well as prognostics and health management problems. Towards this goal, we start with a comprehensive classification of uncertainty types, sources, and causes pertaining to UQ of ML models. Next, we provide a tutorial-style description of several state-of-the-art UQ methods: Gaussian process regression, Bayesian neural network, neural network ensemble, and deterministic UQ methods focusing on spectral-normalized neural Gaussian process. Established upon the mathematical formulations, we subsequently examine the soundness of these UQ methods quantitatively and qualitatively (by a toy regression example) to examine their strengths and shortcomings from different dimensions. Then, we review quantitative metrics commonly used to assess the quality of predictive uncertainty in classification and regression problems. Afterward, we discuss the increasingly important role of UQ of ML models in solving challenging problems in engineering design and health prognostics. In conclusion, two case studies with source codes available on GitHub are used to demonstrate these UQ methods and compare their performance in the life prediction of lithium-ion batteries at the early stage (case study 1) and the remaining useful life prediction of turbofan engines (case study 2).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

All 2D Material Printed Diodes and Circuits on Paper for Sustainable Electronics

Sustainable electronics aim to reduce environmental impact by using ecofriendly materials, energy-efficient manufacturing, and recyclable components. However, existing approaches rely on complex, resource-intensive methods, rare metals, or nanomaterials with limited stability as well as plastic substrates, raising sustainability issues. Solution-processed two-dimensional (2D) materials offer a promising alternative: water-based and biocompatible conductive, semiconductive, and insulating 2D material inks can be produced with scalable techniques and are suitable for the fabrication of fully printed devices on low-cost and biodegradable paper substrates. However, 2D material only and fully printed diodes on paper have not yet been reported. Here, we demonstrate fully inkjet-printed 2D material-based diodes on paper using metal-insulator-semiconductor and metal-insulator-metal-semiconductor architectures. Water-based graphene and MoS2 inks, prepared by liquid-phase exfoliation, are used for the metallic and insulating films, while electrochemical exfoliation is used to produce the semiconducting MoS2 ink. The highest forward-to-reverse current ratio obtained is 330 (at ±2 V), while the forward current density is 1 mA/cm2 (at 1 V), making the diode performance comparable to the best solution-processed diodes reported so far. However, in contrast to previous works, fabrication occurs entirely at room temperature and ambient pressure, without using high-pressure sputtering, thermal evaporation, and any precious metal ink. The devices maintain stable performance under bending up to strain of 4% over 10,000 cycles. Finally, the diodes are successfully integrated with other 2D-material based electrical components to realize fully printed RC circuits, differentiators, integrators, and AC-to-DC converters onto paper, hence demonstrating the suitability of our approach for sustainable and disposable integrated circuits.

2D materials↗
DOE OSTI2023

IPL-Annealed Mixed-Cation Perovskites with Robust Coating Window toward Scalable Manufacturing of Commercial Perovskite Solar Cells

Perovskite solar cells (PSCs) are a promising alternative solar technology, but the technical challenges of (1) stability/durability, (2) efficiency at scale, and (3) manufacturability must be overcome to achieve widespread PSC commercialization. The challenge of balancing solution ink formulation and scalable manufacturing is often overlooked in the literature, where focus is on adopting inks from processes that will not scale. In this study, we apply a classical roll-to-roll manufacturing perspective, utilizing both compositional engineering and intense pulsed light (IPL) annealing, to develop a mixed-cation perovskite ink with a robust coating window that simultaneously solve issues of stability and manufacturability for PSCs. Our method resulted in blade-coated, flexible, mixed-cation PSCs on ITO-PET substrates with a champion power conversion efficiency (PCE) efficiency of 16.7% using IPL annealing of the absorber layer and, to our knowledge, is one of the fastest processing methods for the perovskite layer. This overall reduction in processing time with a stable ink represents an advance toward the scaled production of perovskite solar cells on flexible substrates.

flexible perovskite solar cells↗
DOE OSTI2024

Supercharge NY

The Energy Program for Innovation Clusters (EPIC) Supercharge NY enabled The Clean Fight to execute an inaugural accelerator program focused on enabling world-class, growth-stage energy storage companies to successfully scale deployments and establish domestic manufacturing pathways in New York State. The Clean Fight has developed and tested a successful accelerator model designed to reduce the barriers growth-stage climate tech companies face by collapsing the sales cycle to scaling solutions at speed. The Clean Fight’s Supercharge NY project allowed for the exploration into the understanding of New York-focused energy storage opportunities, challenges, and methods for enabling successful projects. The Clean Fight’s Supercharge NY project enabled high-touch matchmaking with industry leading customer and capital partners, technical assistance to facilitate scaling supply chain and manufacturing capacity, and access to non-dilutive funding for first-of-a-kind or demonstration projects in New York State. The results of the program provide a public benefit by accelerating deployments of energy storage to provide value-added energy services and sustainability benefits to communities while boosting economic opportunity and job creation for all.

25 ENERGY STORAGE↗
DOE OSTI2020

Development of Perovskite (PVSK) Technology Related to Solar Cell Manufacturing Equipment (CRADA CRD-18-733 Final Report)

This CRADA between Energy Everywhere and NREL is to develop a process to fabricate flexible photovoltaic modules using a solution coated PVSK absorber with interlayers comprising materials deposited by economically feasible methods. Energy Everywhere™ will replicate and scale this process in Berkeley, California where it will ultimately commercialize the process, fabrication equipment, and PV modules.

14 SOLAR ENERGY↗
DOE OSTI2024

Anti-symmetric and positivity preserving formulation of a spectral method for Vlasov-Poisson equations

We analyze the anti-symmetric properties of a spectral discretization for the one-dimensional Vlasov-Poisson equations. The discretization is based on a spectral expansion in velocity with the symmetrically weighted Hermite basis functions, central finite differencing in space, and an implicit Runge Kutta integrator in time. The proposed discretization preserves the anti-symmetric structure of the advection operator in the Vlasov equation, resulting in a stable numerical method. We apply such discretization to two formulations: the canonical Vlasov-Poisson equations and their continuously transformed square-root representation. The latter preserves the positivity of the particle distribution function. We derive analytically the conservation properties of both formulations, including particle number, momentum, and energy, which are verified numerically on the following benchmark problems: manufactured solution, linear and nonlinear Landau damping, two-stream instability, bump-on-tail instability, and ion-acoustic wave.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Designing a drone delivery network with automated battery swapping machines

Drones are projected to alter last-mile delivery, but their short travel range is a concern. In this study, we propose a drone delivery network design using automated battery swapping machines (ABSMs) to extend ranges. The design minimizes the long-term delivery costs, including ABSM investment, drone ownership, and cost of the delivery time, and locates ABSMs to serve a set of customers. We build a mixed-integer nonlinear program that captures the nonlinear waiting time of drones at ABSMs. To solve the problem, we create an exact solution algorithm that finds the globally optimal solution using a derivative-supported cutting-plane method. To validate the applicability of our program, we conduct a case study on the Chicago Metropolitan area using cost data from leading ABSM manufacturer and geographical data from the planning and operations language for agent-based regional integrated simulation (more commonly known as POLARIS). A sensitivity analysis identifies that ABSM service times and costs are the key parameters impacting the long-term adoption of drone delivery.

25 ENERGY STORAGE↗