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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.

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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Critical review and future prospects for desiccant coated heat exchangers: Materials, design, and manufacturing

Solid desiccant dehumidification is a promising alternative to vapor compression-based air-dehumidification to reduce energy consumption and improve air quality. Desiccant coated heat exchanger (DCHE), as one type of solid desiccant dehumidification system, can improve system performance and efficiency. The thermal performance and moisture removal capability of the DCHE greatly influence its dehumidification performance.The present work aims to critically analyze the designs, materials, and manufacturing methods of heat exchangers used for solid desiccant coating and look into recent developments in regular heat exchangers, potentially deployed as a substrate for DCHE applications. A comprehensive literature review of publications regarding solid desiccant materials, heat exchangers, manufacturing and coating methods, binder materials, and the performance of heat exchangers has been developed. Alternative heat exchangers are described as better options than fin and tube heat exchangers that have been considered thus far for DCHE applications. Additionally, the heat exchanger's manufacturing process and materials over their thermal and mass exchange performance have been analyzed. Despite the widespread use of fin and tube heat exchangers for solid desiccant coating, recent developments in heat exchanger design, and related fields such as manufacturing methods and materials, open the possibilities for their application in solid desiccant dehumidification systems. Lastly, the authors provide their outlook on possible developments of DCHE technology, aiming to increase systems' energy and dehumidification performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

State-by-State comparison of combined heat and power to photovoltaic installations at manufacturing facilities with heat and power loads

Manufacturing facilities with large electricity and steam loads commonly meet those loads with a grid and boiler (GB) system configuration. In this study, two alternatives, a natural gas turbine cycle driven combined heat and power (CHP) system configuration and a grid boiler system augmented with photovoltaics (GB-PV), are investigated sustainable manufacturing in reference to the GB system configuration. For this purpose, their discounted payback period (DPP), carbon dioxide (CO 2 ) and nitrogen oxides (NO x ) emission reductions, and primary fossil energy impacts are calculated. The major contribution of this study is that it directly compares the application of both CHP and PV technologies at an assumed manufacturing facility in all 50 states of the United States. This highlights the location-specific impacts of the facility. The examined manufacturing facility utility requirements are 5 MW of power and over 12,000 kg/h of 250 kPa and 400 K saturated steam. A DPP of less than 25 years, the technology lifetime, is found in 44 states for the CHP system configuration and 6 states for the GB-PV system configuration. GB-PV and CHP cost-effectively reduce CO 2 in 44 and 38 states, respectively. CHP is better for NO x reduction, whereas GB-PV is better for primary fossil energy reduction.

14 SOLAR ENERGY↗
DOE OSTI2024

Viability of Additively Manufactured Electrodes for Lithium-Ion Batteries

As the global economy becomes increasingly electrified, the demand for batteries and energy storage is expected to rise significantly, particularly in the transportation and electricity sectors. Lithium-ion batteries (LIBs) are currently the most advanced and widely used technology in this field. Traditionally, LIBs are manufactured using simple 2D planar geometries to maximize production efficiency and minimize costs. However, this approach limits energy density due to the restricted design flexibility of the electrodes. Additive manufacturing (AM) offers a promising solution to enhance the energy density and efficiency of LIBs by enabling the design of architectures that reduce diffusive losses and allow for a greater amount of active material to be incorporated within the same device footprint, thereby minimizing the use of inactive materials. Different AM techniques come with their own set of limitations, including printing speed, material compatibility, and scale, which must be considered when designing electrodes. Scalable and cost-effective methods are particularly important for electric vehicle batteries, while achieving higher energy densities in microbatteries is crucial for the miniaturization of wearable electronics and medical devices. Here, in this study, we simulate various 3D porous electrode designs for LIBs using graphite and nickel manganese cobalt oxide (NMC) electrodes. These designs are selected to represent structures that could be produced using different AM techniques, such as direct ink writing, fused deposition modeling, and stereolithography. Our results indicate that at higher charging rates and increased areal mass loading, 3D structures can outperform traditional 2D electrodes, although the benefits may diminish with more complex designs that are harder to manufacture. The observed gains in energy density are attributed to improved electrode utilization and reduced diffusive energy losses. This comprehensive analysis of structure–performance relationships will provide valuable insights to guide future research on 3D designs, material selection, and AM techniques for additively manufactured battery electrodes.

25 ENERGY STORAGE↗
DOE OSTI2018

Revealing particle-scale powder spreading dynamics in powder-bed-based additive manufacturing process by high-speed x-ray imaging

Powder spreading is a key step in the powder-bed-based additive manufacturing process, which determines the quality of the powder bed and, consequently, affects the quality of the manufactured part. However, powder spreading behavior under additive manufacturing condition is still not clear, largely because of the lack of particle-scale experimental study. Here, we studied particle-scale powder dynamics during the powder spreading process by using in-situ high-speed high-energy x-ray imaging. Evolution of the repose angle, slope surface speed, slope surface roughness, and the dynamics of powder clusters at the powder front were revealed and quantified. Interactions of the individual metal powders, with boundaries (substrate and container wall), were characterized, and coefficients of friction between the powders and boundaries were calculated. The effects of particle size on powder flow dynamics were revealed. Here, the particle scale powder spreading dynamics, reported here, are important for a thorough understanding of powder spreading behavior in the powder-bed-based additive manufacturing process, and are critical to the development and validation of models that can more accurately predict powder spreading behavior.

42 ENGINEERING↗
DOE OSTI2024

Autoregressive distributed lag-based dynamic uniformity modeling and monitoring approaches for superconductor manufacturing

High-temperature superconductors (HTS), known for their high efficiency and low energy loss, have found profound applications across various fields, driving the demand for long, uniformly performing tapes. However, ensuring uniform performance over extended lengths of HTS tapes, often characterized by the consistency of critical current, remains challenging due to fluctuations in growth conditions during manufacturing. Here, to elucidate the mechanisms underlying variations in tape uniformity and enable real-time monitoring of associated parameters, we propose an Autoregressive Distributed Lag (ADL)-based Dynamic Uniformity Modeling and Monitoring (ADUM2) approach. This method integrates uniformity measurement, the identification of critical process parameters and real-time monitoring within the manufacturing process. The ADUM2 approach is applied to the advanced metal organic chemical vapor deposition (A-MOCVD) process, a pilot-scale method for superconductor manufacturing. Our model demonstrates superior performance compared to benchmark methods, accounting for over 80% of the total variance in the data and identifying 13 key process parameters influencing the uniformity of HTS tapes. This study offers significant insights into the high-temperature superconductor manufacturing process and holds the potential to facilitate the production of cost-effective, uniformly performing long superconducting tapes in the future.

autoregressive distributed lag analysis↗
DOE OSTI2026

Additive Manufacturing of Cryogenic Austenitic Steel JK2LB via Wire-Fed Directed Energy Deposition (DED) for Fusion Energy Applications

This study explores the feasibility of fabricating cryogenic austenitic steel JK2LB via both laser-based directed energy deposition (laser-DED) and arc-based directed energy deposition (arc-DED) additive manufacturing processes for potential application in fusion reactors. JK2LB, a low-nickel, high-manganese stainless steel developed for ITER, offers excellent cryogenic toughness, radiation resistance, and decay-to-clearance characteristics. Although JK2LB was originally designed to endure cyclic stresses at cryogenic temperatures in tokamaks, its low-temperature mechanical integrity and radiation tolerance also make it a promising candidate for structural components, such as the coil case/support structure in nonplanar high-temperature superconducting magnet assemblies in stellarators. Directed energy deposition (DED) additive manufacturing was selected for this study due to its capability to fabricate large structures with complex geometries. Here, to address the long lead time and high cost associated with acquiring conventional JK2LB solid wire, JK2LB powder-cored wire was developed as the feedstock material. Testing blocks were then fabricated using both wire-fed laser-DED and arc-DED processes. Microstructural and compositional analyses revealed that both DED approaches yield fully austenitic phase and columnar grain structures. Mechanical testing at room temperature revealed that both DED routes achieved yield strength and elongation comparable to those of conventionally processed JK2LB via vacuum melting, electroslag remelting, extrusion, and drawing, though ultimate tensile strength was reduced due to Mn loss and large columnar grains. As a study mainly focusing on the additive manufacturing process, this work demonstrates the potential of additive manufacturing for fusion energy applications and provides a basis for optimization and future cryogenic mechanical evaluation.

Cryogenic steel↗
DOE OSTI2019

Multi-solution nature of topology optimization and its application in design for additive manufacturing

The purpose of this paper is to introduce the multi-solution nature of topology optimization (TO) as a design tool for additive manufacturing (AM). The sensitivity of topologically optimized parts and manufacturing constraints to the initial starting point of the optimization process leading to structures with equivalent performance is explored. A modified bi-directional evolutionary structural optimization (BESO) code was used as the numerical approach to optimize a cantilever beam problem and reduce the mass by 50 per cent. Several optimized structures with relatively equivalent mechanical performance were generated by changing the initial starting point of the TO algorithm. These optimized structures were manufactured using fused deposition modeling (FDM). The equivalence of strain distribution in FDM parts was tested with the digital image correlation (DIC) technique and compared with that from the modified BESO code.The results confirm that TO could lead to a wide variety of non-unique solutions based on loading and manufacturability constraints. The modified BESO code was able to reduce the support structure needed to build the simple two-dimensional cantilever beam by 15 per cent while keeping the mechanical performance at the same level. Finally, the originality of this paper lies in introduction and application of the multi-solution nature of TO for AM as a design tool for optimizing structures with minimized features in the overhang condition and the need for support structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Digital Twin Approach to Study Additive Manufacturing Processing Using Embedded Optical Fiber Sensors and Numerical Modeling

One of the major challenges for metal-powder-based additive manufacturing is measuring and mitigating residual strain induced during the manufacturing processes. This article reports distributed fiber optic sensors embedded in Inconel alloy components as experimental means to validate numerical models of additive manufacturing process. Electroplating was used to deposit a metal protective jacket onto standard telecom single-mode fibers for strain measurements, Fiber sensors were embedded in an Inconel alloy substrate using the laser engineered net shaping (LENS) process. Here by using a Rayleigh-scattering optical frequency domain reflectometer (OFDR), temperature changes, and residual strain in the metal substrate were monitored with 5 mm spatial resolution during the LENS process. Using finite element analysis, temperature and strain profiles induced by the LENS deposition processes were also numerically studied. Discrepancies between the simulated temperature and strain profiles and those measured directly were less than 10%. Results presented in this article demonstrates a digital twin approach to fuse modeling results with distributed fiber sensor measurement data to study additive manufacturing process toward design and fabrication process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

UIR-Net: Object Detection in Infrared Imaging of Thermomechanical Processes in Automotive Manufacturing

Thermomechanical processes (TMPs) such as resistance spot welding (RSW) and hot stamping are widely used in automotive manufacturing. Recent advancement in sensing technology has led to an increasing adoption of thermographic cameras to capture the infrared (IR) radiation of a metal part (or component of a part) during its thermomechanical processing or immediately after the process when the part is still hot. Detecting the object(s) of interest from raw IR images is an essential step in analyzing these data. Deep learning (DL) has been a recent success for object detection (OD), but the application of DL-based OD for industrial IR images in manufacturing is largely lagging behind. The major contribution of this work, which is also the distinction from previous OD studies, is the capability of building the OD model with unlabeled IR images, i.e., imaging data without accurate information indicating the object position. Here, the architecture of Unsupervised IR Image Net (UIR-Net) is designed to accommodate the unique characteristics of IR images from TMPs in manufacturing. This study presents a novel method for OD in unlabeled IR images from TMPs. The proposed method, called UIR-Net, consists of two components: label generation and DL model construction. Two case studies from automotive manufacturing, RSW and hot stamping, are reported to demonstrate the feasibility and effectiveness of the proposed method.

42 ENGINEERING↗
DOE OSTI2015

SU-E-I-19: Optimization of Low Contrast Detectability Across Two CT Manufacturers

Purpose: Our goal was to evaluate low contrast detectability (LCD) for abdominal CT protocols across two CT scanner manufacturers, while producing a similar noise texture and CTDIvol for acquired images. Methods: A CIRS tissue equivalent LCD phantom containing three columns of 7 spherical targets, ranging from 10 mm to 2.4 mm, that are 5, 10, and 20 HU below the background matrix (HUBB) was scanned using two a GE HD750 64 slice scanner and a Siemens Somatom Definition AS 64 slice scanner. Protocols were designed to deliver a CTDIvol of 12.26 mGy and images were reconstructed with FBP, ASIR and Sapphire. Comparisons were made with those algorithms that had matching noise power spectrum peaks (NPS). NPS information was extracted from a previously published article that matched NPS peak frequencies across manufacturers by calculating the NPS from uniform phantom images reconstructed with several IR algorithms. Results: The minimum detectable lesion size in the 20 HUBB and 10 HUBB column was 6.3 mm, and 10 mm in the 5 HUBB column for the GE HD 750 scanner. The minimum detectable lesion size in the 20 HUBB column was 4.8 mm, in the 10 HUBB column, 9.5 mm, and the 5 HUBB column, 10 mm for the Siemens Somatom Definition AS. Conclusion: Reducing radiation dose while improving or maintaining LCD is possible with application of IR. However, there are several different IR algorithms, with each generating a different resolution and noise texture. In multi-manufacturer settings, matching only the CTDIvol between manufacturers may Result in a loss of clinically relevant information.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Design, Manufacture, and Experimental Serviceability Validation of ITER Blanket Components

In 2014, the Russian Federation and the ITER International Organization signed two Procurement Arrangements (PAs) for ITER blanket components: 1.6.P1ARF.01 “Blanket First Wall” of February 14, 2014, and 1.6.P3.RF.01 “Blanket Module Connections” of December 19, 2014. The first PA stipulates development, manufacture, testing, and delivery to the ITER site of 179 Enhanced Heat Flux (EHF) First Wall (FW) Panels intended for withstanding the heat flux from the plasma up to 4.7MW/m{sup 2}. Two Russian institutions, NIIEFA (Efremov Institute) and NIKIET, are responsible for the implementation of this PA. NIIEFA manufactures plasma-facing components (PFCs) of the EHF FW panels and performs the final assembly and testing of the panels, and NIKIET manufactures FW beam structures, load-bearing structures of PFCs, and all elements of the panel attachment system. As for the second PA, NIKIET is the sole official supplier of flexible blanket supports, electrical insulation key pads (EIKPs), and blanket module/vacuum vessel electrical connectors. Joint activities of NIKIET and NIIEFA for implementing PA 1.6.P1ARF.01 are briefly described, and information on implementation of PA 1.6.P3.RF.01 is given. Results of the engineering design and research efforts in the scope of the above PAs in 2015–2016 are reported, and results of developing the technology for manufacturing ITER blanket components are presented.

42 ENGINEERING↗
DOE OSTI2019

Rheological survey of carbon fiber-reinforced high-temperature thermoplastics for big area additive manufacturing tooling applications

Carbon fiber (CF)-reinforced thermoplastic composites have been widely used in different structural applications due to their superior thermal and mechanical properties. The big area additive manufacturing (BAAM) system, developed at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility, has been used to manufacture several composite components, demonstration vehicles, molds, and dies. These components have been designed and fabricated using various CF-reinforced thermoplastics. In this study, the dynamic rheological and mechanical properties of a material commonly used in additive manufacturing, 20 wt% CF-acrylonitrile butadiene styrene (ABS), as well as three CF-reinforced high-temperature polymers, 25 wt% CF-polyphenylsulfone (PPSU), 35 wt% CF-polyethersulfone (PES), and 40 wt% CF-polyphenylene sulfide (PPS), used to print molds were investigated. The viscoelastic properties, namely storage modulus, loss modulus, tan delta, and complex viscosity, of these composites were studied, and the rheological behavior was related to the BAAM extrusion and bead formation process. The results showed 20 wt% CF-ABS and 40 wt% CF-PPS to display a more dominant elastic component at all frequencies tested while 25 wt% CF-PPSU and 35 wt% CF-PES have a more dominant viscous component. This viscoelastic behavior is then used to inform the deposition and bead formation process during extrusion on the BAAM system.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Real time PV manufacturing diagnostic system

The main obstacle Photovoltaic (PV) industry is facing at present is the higher cost of PV energy compared to that of fossil energy. While solar cell efficiencies continue to make incremental gains these improvements are so far insufficient to drive PV costs down to match that of fossil energy. Improved in-line diagnostics however, has the potential to significantly increase the productivity and reduce cost by improving the yield of the process. On this Phase I/Phase II SBIR project MicroXact developed and demonstrated at CIGS pilot manufacturing line a high-throughput in-line PV manufacturing diagnostic system, which was verified to provide fast and accurate data on the spatial uniformity of thickness, an composition of the thin films comprising the solar cell as the solar cell is processed reel-to-reel. In Phase II project MicroXact developed a stand-alone system prototype and demonstrated the following technical characteristics: 1) ability of real time defect/composition inconsistency detection over 60cm wide web at web speeds up to 3m/minute; 2) Better than 1mm spatial resolution on 60cm wide web; 3) an average better than 20nm spectral resolution resulting in more than sufficient sensitivity to composition imperfections (copper-rich and copper-poor regions were detected). The system was verified to be high vacuum compatible. Phase II results completely validated both technical and economic feasibility of the proposed concept. MicroXact’s solution is an enabling technique for in-line PV manufacturing diagnostics to increase the productivity of PV manufacturing lines and reduce the cost of solar energy, thus reducing the US dependency on foreign oil while simultaneously reducing emission of greenhouse gasses.

14 SOLAR ENERGY↗
DOE OSTI2013

Supply Chain and Blade Manufacturing Considerations in the Global Wind Industry

Over the past decade, significant wind manufacturing capacity has been built in the United States in response to an increasingly large domestic market. Recent U.S. manufacturing production levels exceed anticipated near-term domestic demand for select parts of the supply chain, in part due to policy uncertainty, and this is resulting in some restructuring in the industry. Factor location decisions are influenced by a combination of quantitative and qualitative factors; proximity to end-markets is often a key consideration, especially for manufacturers of large wind turbine components. Technology advancements in the wind sector are continuing, and larger blade designs are being pursued in the market, which may increase U.S.-based manufacturing opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Advanced Manufacturing for Thermal and Environmental Control Systems: Achieving National Energy Goals

This project was part of a regional initiative in the five counties of Central New York (CNY) that received funding from the U.S. Department of Energy (DOE) and four other federal agencies through the 2012 Advanced Manufacturing Jobs and Innovation Accelerator Challenge (AMJIAC). The CNY initiative was focused on cultivating the emergent regional cluster in “Advanced Manufacturing for Thermal and Environmental Control (AM-TEC).” As one component of the CNY AM-TEC initiative, the DOE-funded project supported five research & development seed projects that strategically targeted: 1) needs and opportunities of CNY AM-TEC companies, and 2) the goal of DOE’s Advanced Manufacturing Office (AMO) to reduce energy consumption by 50% across product life-cycles over 10 years. The project also sought to fulfill the AMO mission of developing and demonstrating new, energy-efficient processing and materials technologies at a scale adequate to prove their value to manufacturers and spur investment. The five seed projects demonstrated technologies and processes that can reduce energy intensity and improve production as well as use less energy throughout their lifecycles. The project was conducted over three years in two 18-month budget periods. During the first budget period, two projects proposed in the original AMJAIC application were successfully completed: Seed Project 1 focused on saving energy in heat transfer processes via development of nano structured surfaces to significantly increase heat flux; Seed Project 2 addressed saving energy in data centers via subzero cooling of the computing processors. Also during the first budget period, a process was developed and executed to select a second round of seed projects via a competitive request for proposals from regional companies and university collaborators. Applicants were encouraged to form industry-academic partnerships to leverage experience and resources of public and private sectors in the CNY region. Proposals were evaluated by a national panel of experts. Three projects were selected for awards and were completed successfully during the second budget period: Seed Project 3 focused on enabling self-powered furnaces to permit residents to shelter in place during power outages; Seed Project 4 addressed development of a novel method of controlling air conditioning systems that could enable flexible load matching in market segments not possible with existing technologies; and Seed Project 5 focused on the creation of smarter occupancy sensors to enable effective highly localized demand based ventilation.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2014

Surrogate Final Technical Report for "Solar: A Photovoltaic Manufacturing Development Facility"

The project goal to create a first-of-a-kind crystalline Silicon (c-Si) photovoltaic (PV) Manufacturing & Technology Development Facility (MDF) that will support the growth and maturation of a strong domestic PV manufacturing industry, based on innovative and differentiated technology, by ensuring industry participants can, in a timely and cost-effective manner, access cutting-edge manufacturing equipment and production expertise needed to accelerate the transition of innovative technologies from R&D into manufacturing.

14 SOLAR ENERGY↗
DOE OSTI2017

Energy Innovation Clusters and their Influence on Manufacturing: A Case Study Perspective

Innovation clusters have been important for recent development of clean energy technologies and their emergence as mature, globally competitive industries. However, the factors that influence the co-location of manufacturing activities with innovation clusters are less clear. A central question for government agencies seeking to grow manufacturing as part of economic development in their location is how innovation clusters influence manufacturing. Thus, this paper examines case studies of innovation clusters for three different clean energy technologies that have developed in at least two locations: solar PV clusters in California and the province of Jiangsu in China, wind turbine clusters in Germany and the U.S. Great Lakes region, and ethanol clusters in the U.S. Midwest and the state of Sao Paulo in Brazil. These case studies provide initial insight into factors and conditions that contribute to technology manufacturing facility location decisions.

14 SOLAR ENERGY↗
DOE OSTI2017

Bio-Manufacturing to market pilot project

The Bio-Manufacturing to Market pilot project was a part of the AMJIAC, the Advanced Manufacturing Jobs and Innovation Accelerator Challenge grant. This internship program set out to further define and enhance the talent pipeline from the University and local Community Colleges to startup culture in East Bay Area, provide undergraduate STEM students with opportunities outside academia, and provide startup companies with much needed talent. Over the 4 year period of performance, the Bio-Manufacturing to Market internship program sponsored 75 undergraduate STEM students who were able to spend anywhere from one to six semesters working with local Bay Area startup companies and DOE sponsored facilities/programs in the biotech, bio-manufacturing, and biomedical device fields.

60 APPLIED LIFE SCIENCES↗