Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “industries”

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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Data from Economic Perspective of Ethanol and Biodiesel Coproduction from Industrial Hemp

In this study, the economics of producing biofuels from an industrial hemp (Cannabis sativa) genotype – 19m96136 was investigated. A lignocellulosic biofuel plant, hourly consuming 85 metric tons of hemp biomass was modeled in SuperPro Designer®. The integrated bioenergy plant produced hemp biodiesel and bioethanol from lipids and carbohydrates, respectively. The structural composition of the industrial hemp plant was analyzed in a previous study. The data obtained was used to simulate feedstock composition in SuperPro Designer®. The simulation results indicated that Hemp containing 2% lipids can yield up to 3.95 million gallons of biodiesel annually. On improving biomass lipid content to 5 and 10%, biodiesel production increased to 9.88 and 19.91 million gallons, respectively. The breakeven unit production cost of hemp biodiesel with 2, 5, and 10% lipid containing hemp was $18.49, $7.87, and $4.13/gallon, respectively. The biodiesel unit production cost when utilizing 10% lipid-containing hemp was comparable to soybean biodiesel at $4.13/gallon. Furthermore, sensitivity analysis revealed the possibility of a 7.80% reduction in unit production cost upon a 10% reduction in hemp feedstock cost. Furthermore, industrial hemp was capable of producing between 307.80 and 325.82 gallons of total biofuels per hectare of agricultural land than soybean.

Conversion↗
DOE OSTI2025

Data for "Evaluating the industrial potential of emerging biomass pretreatment technologies in bioethanol production and lipid recovery from transgenic sugarcane"

The selection of pretreatment methods is critical to achieving high product yields during bioconversion of lignocellulosic biomass. Hydrothermal, soaking-in-aqueous ammonia, and ionic liquid pretreatment methods are viable candidates for minimizing sugar decomposition, permitting the effective hydrolysis of structural carbohydrates, and producing a fermentable substrate suitable for achieving industrial ethanol titers and yields. In this study, the effect of these three pretreatment methods on non-modified sugarcane cultivar CP88-1762 and two transgenic lipid-accumulating sugarcane lines, oilcane 1565 and oilcane 1566, were investigated and compared in terms of lipid recovery, sugar yield, and ethanol yields within the lignocellulosic biomass conversion pipeline. Fed-batch enzymatic hydrolysis at high solid loading yielded hydrolysates capable of supporting industrial bioethanol titers across all conditions. The highest sugar yields were obtained on ammonia-pretreated biomass hydrolysate (253.73 g L−1), followed by hydrothermally pretreated hydrolysate (213.10 g L−1) and ionic liquid-pretreated hydrolysate (154.20 g L−1). Commercially viable ethanol titers of 100.62 g L−1, 64.47 g L−1, and 52.95 g L−1 were achieved from ammonia, hydrothermal, and ionic liquid pretreated hydrolysate with the corresponding ethanol productivities of 2.08 g L−1 h−1, 0.53 g L−1 h−1, and 0.36 g L−1 h−1. The lower acetic acid concentration in ammonia-pretreated hydrolysate may have enhanced its fermentability relative to the hydrothermal pretreatment condition, as indicated by the differences in ethanol titer and productivity. Lower sugar yields and ethanol productivities under the ionic liquid conditions likely resulted from the inhibitory effect of cholinium lysinate. Oilcane 1565 and oilcane 1566 bagasse accumulated over 16- and 3 times higher lipids than the non-modified sugarcane CP88-1762. The total fatty acid content in the oilcane samples was reduced in ammonia and ionic liquid-pretreated bagasse relative to the hydrothermal pretreatment condition. While all pretreatment techniques tested are industrially viable, the observed differences in titer, productivity, and lipid content indicate that careful selection and validation of upstream processing methods can contribute to improved economic and environmental outcomes.

biomass analytics↗
DOE OSTI2026

Advancing Conduction-Cooled 650 MHz SRF Technology for Industrial Accelerators at Fermilab's IARC

The National Nuclear Security Administration (NNSA) funds the Illinois Accelerator Research Center (IARC) at Fermilab in developing a high-power, conduction-cooled Superconducting Radio Frequency (SRF) accelerator tailored for industrial applications requiring robust and efficient operation. A 650 MHz, 1.6 MeV, 20 kW SRF accelerator is currently under development, employing a conduction cooling approach to simplify cryogenic requirements and enhance accessibility for industrial use. The accelerator’s control system is implemented on the Blinky Lite platform, selected for its open-source architecture, secure remote access capabilities, and operational flexibility—attributes advantageous for industrial deployment and sustained operation. A dedicated beamline is designed to measure essential beam parameters and test the integrated performance of the accelerator and control systems, thereby validating their operational readiness for intended applications

Ji, Y. [Fermilab] (ORCID:0000000233981752)↗
DOE OSTI2025

First Results from a Nb3Sn-Coated 1.5-Cell 650 MHz SRF Cavity for Cryogen-Free Industrial Accelerators

First Results from a Nb3Sn-Coated 1.5-Cell 650 MHz SRF Cavity for Cryogen-Free Industrial Accelerators ABSTRACT = Fermilab is advancing the development of a compact, high-power electron beam accelerator using superconducting radio frequency (SRF) technology as a non-radioactive alternative to traditional radiological sources. The current design targets continuous-wave (CW) operation at \SI{1.6}{MeV} and \SI{20}{kW}. To ensure suitability for industrial environments, the system is being designed for cryogen-free operation, driving the adoption of a novel Nb$_3$Sn-coated 1.5-cell SRF cavity operating at \SI{650}{MHz}. This contribution reports on the fabrication, surface preparation, and Nb$_3$Sn coating process of the cavity, as well as first results from vertical test stand (VTS) measurements performed in a liquid helium bath. These initial tests mark a key milestone toward demonstrating the viability of conduction-cooled Nb$_3$Sn SRF cavities for industrial-scale deployment.

Tagdulang, N. [Fermilab]↗
DOE OSTI2024

Clean Industry in China: A Techno-Economic Comparison of Electrified Heat Technologies, Barriers, and Policy Options

China’s manufacturing sector generates 61% of the country’s CO 2 emissions, nearly three-quarters of which is related to industrial process heating. To meet China’s climate targets and attain a zero-carbon industrial sector, decarbonizing these industrial heating processes is a necessity. If China’s electricity grid is similarly decarbonized, direct electrification is the most practical means of supplying this heat efficiently at the required scale.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Communication of industry knowledge, best practices, and lessons learned in the space of cellulosic biofuels plant design, project development and execution and operations. Task 1 report

ExxonMobil Research and Engineering Company, via a technical services agreement, engages Idaho National Laboratory (INL) to provide general industry knowledge, best practices, and lessons learned in cellulosic ethanol plant design, project execution, and operations. INL will also assess publicly proposed cellulosic plant designs. The scope of work will be accomplished in three tasks: Task 1, Communicate industry knowledge; Task 2, Present high-level lessons learned; Task 3, Provide an engineering assessment of publicly proposed ethanol plant designs. This Task 1 report provides a high-level summary of general industry knowledge, best practice, and lessons learned in biomass feedstock logistics and integration with bioconversion processes.

09 BIOMASS FUELS↗
DOE OSTI2020

Solar Industry Update (Q1/Q2 FY2020) [Slides]

Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry, to the solar office staff. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.

14 SOLAR ENERGY↗
DOE OSTI2020

Solar Industry Update (Q2/Q3 2020) [Slides]

Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry, to the solar office staff. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. Government programs supporting the solar industry.

14 SOLAR ENERGY↗
DOE OSTI2021

Solar Industry Update: (H2 2020) [Slides]

Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry, to the solar office staff. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.

14 SOLAR ENERGY↗
DOE OSTI2021

H1 2021 Solar Industry Update

Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry, to the solar office staff. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.

14 SOLAR ENERGY↗
DOE OSTI2021

Advanced High-Strength Steel - Basics and Applications in the Automotive Industry

Challenged to improve safety and fuel economy, automakers continually search for new materials to meet high standards. Several factors drive the material R&D and selection for automotive applications, including safety, fuel efficiency, environmentalism, manufacturability, durability, and quality. In the highly competitive automotive industry, cost is an extremely important factor in material selection. As the motivation to reduce the mass of vehicles continues to grow, automakers seek to maximize the efficiency of their materials selection. Materials in automotive applications are selected to minimize weight while meeting key criteria, including crash performance, stiffness, and forming requirements. Since the 1920s, steel has been the material of choice for automakers worldwide. The weight percentage of steel used in vehicles relative to other materials has grown from around 50% in the early 1980s to about 60% in 2010 for North American light vehicles. Today, steel makes up around 65% of an average automobile’s weight and is the backbone of the entire vehicle. On average, that is 900 kg of steel used per vehicle. To further enhance passenger safety, vehicle performance, and fuel efficiency, reducing the weight of vehicles has become one of the top priorities for the automotive industry. Advanced high-strength steels (AHSSs) are a new generation of steel grades that provide much higher strength and other advantageous properties than other materials while maintaining the high formability required for manufacturing. AHSSs help engineers meet requirements for safety, efficiency, emissions, manufacturability, durability, and quality at a low cost. The relevance of AHSSs is quickly increasing in the automotive industry, and AHSSs are the key material for vehicle mass reduction. Different types of AHSS help parts meet the varied performance demands in different areas of the vehicle, including both the crumple zone and passenger compartment.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Industry Level Integrated Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

The software Fire Risk Investigation in 3D (FRI3D) has been developed over the last 2 years to integrate 3D spatial modeling with existing fire probabilistic risk assessment (PRA) models and fire simulation codes. The goal of this research and development is to automate many of the fire analysis manual tasks to reduce industry efforts in the initial fire modeling and operational costs for the model maintenance and evaluations required during normal plant operations. The tasks for Fiscal Year (FY) 2021 include first testing the FRI3D modeling capabilities by importing an industry fire model into FRI3D and making a 3D model of a complex/high-risk significant area. (For this work, the switchgear room was chosen.) Then, the second task of FY 2021 is to develop a dynamic fire PRA process that can help optimize traditional fire PRA models. The switchgear room model will be used for the dynamic fire PRA work. This report describes the work and insights learned when using FRI3D software to model both a Nuclear Regulatory Report (NUREG) example models and a full industry switchgear room.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Industry-Average Performance for Components and Initiating Events at U.S. Commercial Nuclear Power Plants: 2020 Update

This report documents the quantitative results of the current industry-average performance for components and initiating events (IEs) at U.S. commercial nuclear power plants (NPPs). It represents the third update of the original analysis in NUREG/CR-6928 with data through 2020. Continuous characterization and updating of current industry-average performance with the latest industry data available are important steps in maintaining up-to-date risk models. Typically, data from 1998–2002 were used in NUREG/CR-6928, data from 1998–2010 in the first update, data from 1998–2015 in the second update, and data from 2006–2020 in this update, although many IEs required longer periods for adequate characterization of frequencies in all these analyses. As with NUREG/CR-6928 and previous updates, four types of events are covered in this report: component unreliability (e.g., a pump that fails to start or fails to run), component or train unavailability resulting from test or maintenance outages, special event probabilities covering operational issues (e.g., pump restarts and injection valve re-openings during unplanned demands), and IE frequencies. Results (in the form of beta distributions for failure probabilities upon demand and gamma distributions for rates) are used as inputs to the U.S. Nuclear Regulatory Commission standardized plant analysis risk models covering U.S. commercial NPPs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

MFIX DEM Enhancement for Industry-Relevant Flows (Final Report)

The overall goal of this two-phase project is to implement performance improvements of the Multiphase Flow with Interphase Exchanges (MFIX) Discrete Element Model (DEM) code that enable a transformative shift for industrial use. Prior to this effort, the largest simulations performed using MFIX are O(10 7 ) particles. This falls short of the O(10 9 ) particle simulations that must be completed on a timescale of days or weeks (vs. months or years) to enable simulations with physically-relevant domain sizes to be incorporated into industrial design cycles within five years. This was accomplished by tailoring best-in-class practices to bear on the unique challenges posed by the MFIX-DEM algorithm and code base. Scientific simulations (e.g., in cosmology, turbulent combustion) routinely use massively parallel computing to update far more particles in short wall clock times. Results from Phase 1 (1.5 years in duration) indicated significant gains in speed were possible for a wide range of benchmark cases. Moreover, a survey sent to >35 companies indicates that the timing is ideal for such an enhanced tool, with >80% of the respondents indicating that DEM is already value-added or will be within the next 5 years, and >70% of the respondents indicating that improved speed is the top computational priority. In Phase 2 (3.5 years in duration), the two major barriers that hinder industry from effectively using multiphase Computational Fluid Dynamics (CFD) to cut costs and improve performance, namely computational overhead and confidence in predictions, continued to be addressed. Regarding the former, the results from Phase 1 to guide the effort, with enhancements focused on an improved time-stepping algorithm and particle sorting. Four target problems of 1 billion particles each and increasing complexity were identified: homogeneous cooling, tumbler with continuous particle size distribution, discharge from a rectangular hopper and a cylindrical riser. Each of these were successfully simulated for relevant time scales (on order of seconds) using less than 24 hours of wall clock time. These represent the first 1-billion particle DEM simulations performed with MFIX, namely using the MFIX-Exa code. This code is currently under development at NETL in collaboration with Lawrence Berkeley National Laboratory. Regarding the second barrier on predictive uncertainty, experiments from Phase 1 (interacting nozzles - hydrodynamics only) and Phase 2 (very small-scale segregation experiments) were used to demonstrate the ability of two simplified approaches to uncertainty quantification (UQ). By limiting the number of particles, UQ based on the simplified treatment was compared to standard UQ, which was shown to have much higher computational demands. Experiments were also performed on a pilot-scale stripper unit to provide validation data for future CFD-DEM simulations and UQ.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy

The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Industrial Assessment Center for Energy Efficiency, Smart Manufacturing and Cyber Security of Illinois and Northwestern Indiana Small and Medium Sized Manufacturing Companies and Water Facilities (Final Technical Report)

The University of Illinois Chicago (UIC) established and implemented a U.S. Department of Energy (DOE) sponsored Industrial Assessment Center (IAC) from September 1, 2016 through December 31, 2021. The established UIC IAC focused on providing 1) technical assistance to small and medium-sized enterprises (SMEs) and water and wastewater facilities in Illinois and northwestern Indiana and 2) education and training university students developing the future energy workforce. The technical assessments incorporated energy efficiency, increasing productivity via smart manufacturing, energy management systems, enhancing on-site cyber security practices, and the promotion of DOE best practices and tools. The educational training enabled UIC faculty and staff to provide classroom education, exposure to industry research, multiple targeted training sessions, real world experience with industry professionals, and live training to implement professional grade audits and recommendations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

U.S. Industrial and Commercial Motor System Market Assessment Report. Volume 3: Energy Saving Opportunity

This report seeks to inform the potential for motor systems to support decarbonization by estimating their potential energy, electricity cost, and CO 2 emissions reduction potential from adoption of proven energy efficiency actions and advanced technologies. This is the third and final report in a series of reports disseminating the findings of the U.S. Department of Energy’s (DOE’s) Motor System Market Assessment (MSMA). The MSMA and this report focus on polyphase motor systems greater than or equal to 1 horsepower (hp) in the industrial and commercial sectors. In the U.S. Industrial and Commercial Motor System Market Assessment Report Volume 1: Characteristics of the Installed Base (Volume 1 report), it was determined that these motor systems consume more than 1,000 terawatt-hours (TWh) annually. This equates to 29% of the U.S. electric grid load and results in 765 million metric tons (MMT) of CO 2 emissions and $166 billion in electricity costs. This report finds that substantial reductions to these energy, cost, and emissions impacts are possible, with three areas of significant opportunity being (1) improved load matching, (2) replacing older inefficient motors with more efficient motors, and (3) improving the condition of fluid (e.g., air, water, compressed air) distribution systems. A summary of the savings potential from these three opportunities placed within the context of the overall consumption for motor systems is illustrated in Figure ES 1 (industrial) and Figure ES 2 (commercial).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗