Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Commercialization”

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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Decarbonization of heat pump dual fuel systems using a practical model predictive control: Field demonstration in a small commercial building

In the transition from fossil fuel to electrified heating, a concerning trend is emerging in certain regions of the US. Owners of buildings with gas-based systems leave them in place after adding heat pumps (HPs). Existing control solutions for these hybrid (dual fuel) systems are rudimentary and fall short of realizing the full carbon reduction potential of these systems. Model predictive control (MPC) is often regarded as the benchmark for achieving optimal control in integrated systems. However, in the case of small-medium commercial buildings (SMCBs), the control and communication infrastructure required to facilitate the implementation of such advanced controls is often lacking. This paper presents a field implementation of easy-to-deploy MPC for a dual fuel heating system consisting of HPs and a gas-fired furnace (GF) for SMCBs. The control system is deployed on an open-source middleware platform and utilizes low-cost sensor devices to be used for real SMCBs without major retrofits. Here, we demonstrated this MPC in a real office building with 5 HPs and 1 GF for 2 months. The test results showed that MPC reduced 27% of cost while completely eliminating GF usage by shifting 23% of the thermal load from occupied-peak time to non-occupied-non-peak times.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Regional difference and related cooling electricity savings of air pollutant affected natural ventilation in commercial buildings across the US

Maintaining indoor air pollutants under acceptable levels is significant to protect occupants from exposure to excessive air pollutants in natural ventilation. In this paper, using the representative air pollutant concentration data, we present the natural ventilation usability with associated cooling energy saving potentials in different location settings (urban and city center, suburban and rural) of the US under the influence of local weather conditions and major outdoor air pollutants, i.e. PM2.5, PM10 and ozone. It is found that the impacts of air pollutants on natural ventilation are usually higher in urban/suburban areas than rural areas (up to 25% difference) with the PM2.5 being the most significant outdoor air pollutant affecting natural ventilation usage. Furthermore, ozone could become increasingly influential on natural ventilation as moving from urban to suburban/rural areas. As to the cooling energy saving considering the impacts of outdoor air pollutants, natural ventilation is estimated to save approximately 10%–40% cooling energy (800–2600 kWh per small commercial building) annually in different location settings of investigated areas across the US. The following economic analysis demonstrates that these electricity savings lead to approximately 80–540 dollars annual savings of building operation cost per building. If the time of use rate is adopted, these cost savings could further increase by approximately 20% (Los Angeles) to more than 50% (Albuquerque) depending on different rate structures, which further demonstrates the potential of adopting natural ventilation as a sustainability measurement with benefits for building owners without compromising occupants health.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Energy-efficient carbon capture from industrial point sources via commercially available green solvent and hollow fiber membrane contactors

Solvent-based absorption systems have emerged in the carbon capture space due to their high absorption capacities, reusability, and favorable energy requirements. Using diethyl sebacate as a solvent for pre- and post-combustion carbon capture has advantages over other solvents, including high hydrophobicity, low viscosity, low vapor pressure, high CO 2 solubility, high CO 2 selectivity, and being commercially available in large quantities. Despite these advantageous properties, the use of diethyl sebacate as a solvent for post-combustion carbon capture has not been studied in detail. To examine the capability of diethyl sebacate, a scalable, energy-efficient, hollow fiber membrane (microporous polypropylene and polyvinylidene fluoride) contactor (HFMC)-based process with low-cost and high surface area is investigated. A purity of 95.3 % CO 2 with 46 % recovery in one absorption stage was achieved, with a permeate flux over one magnitude greater than using a deep eutectic solvent in the same system. Technoeconomic analysis determined a ∼ 0.8 GJ per ton of CO 2 at a processing cost of ∼$93 per ton of CO 2 . Results from this work underscore the potential for utilizing green solvents in HFMC-based separation processes for effective carbon capture and provide a pathway towards practical deployment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Direct air capture with bis-iminoguanidines: From discovery to commercialization

Here, research on direct air capture (DAC) of CO 2 at Oak Ridge National Laboratory (ORNL) over the past five years is highlighted, starting with the initial discovery, continuing with fundamental and applied research, and concluding with commercialization by teaming up with industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Cyclic oxidation behavior of selected commercial NiCr-alloys for engine exhaust valves in wet air environment between 800 and 950 °C

In this work, the impact of water vapor on the cyclic oxidation behavior of four commercial Ni-based superalloys (N80A, N90, R41 and H282) was investigated between 800 and 950°C. Oxidation- and volatilization-induced Cr loss accelerated the transition from protective and adherent oxide formation (Cr 2 O 3 ) to mixed oxides that significantly spalled at 950°C for H282 and R41. The accelerated oxidation, Cr depletion, and spallation susceptibility for R41 and to a lesser extent for H282 compared to N80A and N90 was related to the higher fraction of γ’, which led to increased Ti incorporation into the Cr 2 O 3 scale in the presence of water vapor.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Superconducting properties of commercially available solders for low-field applications

Solders with superconducting transitions around 4K are useful in low magnetic field environments for AC current leads or in electrical and mechanical bonds. Accurate knowledge of these solders’ superconducting properties is essential for improving high precision experiments. We have measured the electrical resistance of five commercially-available eutectic or near-eutectic solders: 50%Sn-50%Pb, 60%Sn-40%Pb, 60%Sn-40%Pb-0.3%Sb, 52%In-48%Sn, and 96.5%Sn-3.5%Ag, down to 2.3K and in applied magnetic fields from 0 to 0.1 T . We report critical temperatures T c (B), 90%–10% transition widths ΔT c , and zero-temperature critical fields B c,0 . Our best candidate for low-loss AC current wiring in low fields is 50%Sn-50%Pb, which has a zero-field T c,0 = 7.1K (with ΔT c = 0.6 K), and remained high at T c (0.1 T) = 6.9K (ΔT c = 0.6K ). We also report, for the first time, T c and B c of 60%Sn-40%Pb-0.3%Sb and B c,0 of 96.5%Sn-3.5%Ag. Our T c,0 - 3.31K (ΔT c = 0.08K) for 96.5%Sn-3.5%Ag disagrees with a widely adopted value.

Hickman, C. [North Carolina State University, Rale↗
DOE OSTI2021

Investigating the durability of a direct methanol fuel cell equipped with commercial Platinum Group Metal-free cathodic electro-catalysts

For the first time a long-term (500 h) durability study in direct methanol fuel cells (DMFCs) is carried out on a Platinum Group Metal-free (PGM-free) cathodic electro-catalyst commercially available on market. The electro-catalyst is tested for 500 h at a fixed cell voltage (0.3 V), recording the polarization curves during the operation. A drastic decrease in performance is observed after the first 100 h (from 220 to 75 mA cm –2 ); afterwards, the decrease is flatter, passing from 75 to 25 mA cm –2 (at 500 h). The causes of this performance degradation are investigated by postmortem physicochemical analyzes, such as X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM) and scanning electron microscopy (SEM) with X-ray energy dispersive analysis (EDX). Finally, possible reasons of degradation are indicated to be PGM-free catalyst aggregation, carbon and nitrogen species decrease, Ruthenium dissolution and migration from the anode to the cathode, poisoning both membrane and cathode catalyst.

25 ENERGY STORAGE↗
DOE OSTI2020

Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings

The U.S. power grid is transforming to become smarter, cleaner, and more effi- cient. This is leading to the addition of significant distributed variable renew- able generation. Due to the variable nature of renewable generation, the short- and long-term supply-demand imbalances are less predictable, and conventional approaches to mitigating the imbalance will not be efficient or cost-effective. To address this challenge, transactive control technologies have been proposed which balance energy generation and consumption with market activity and in- frastructural limitations. Transactive control requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical gray- and black-box models have been widely used to express flexibility, and although these approaches are generally easy to construct and simple to use, they do not capture the non-linear behavior that some end-use loads represent . Machine learning approaches have been proposed to address this limitation. Although deep learning approaches for forecasting end-use loads have been explored, certain aspects of the application of deep models to load forecasting are not well understood. These aspects include how much training data is required, and how models should be structured and trained. To that end, this work explores how to approach applying deep recurrent neural networks to short-term electrical load forecasting with a case study of four commercial office buildings. We identify data requirements for training accurate models of whole building electricity use conditioned on outdoor temperature, provide insight into model hyperparameter sensitivity, and demonstrate how readily models can be generalized to unseen buildings.

Skomski, Elliott↗
DOE OSTI2021

A zone-level occupancy counting system for commercial office spaces using low-resolution time-of-flight sensors

Understanding the locations of occupants in a commercial built environment is critical for realizing energy savings by delivering lighting, heating, and cooling only where it is needed. In this paper, we present an indoor occupancy counting system using a sparse array of inexpensive, low-resolution, and privacy-preserving time-of-flight sensors. We develop and validate an algorithm for zonal occupancy counting that can deal with multiple people walking underneath the sensors in arbitrary directions, and evaluate the system both in realistic simulations of office spaces and in a real-world installation. Finally, we found that our system has an error rate of around 0.4%, resulting in highly accurate person localization and zone counting using only a few sensors per space.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Performance analysis and comparison of data-driven models for predicting indoor temperature in multi-zone commercial buildings

Building thermal models, which characterize the properties of a building’s envelope and thermal mass, are essential for accurate indoor temperature and cooling/heating demand prediction. Because of their flexibility and ease of use, data-driven models are increasingly used. Here, this study compared and analyzed the performance of gray-box (resistance-capacitance) and black-box (recurrent neural network) models for predicting indoor air temperature in a real multi-zone commercial building. The developed resistance-capacitance model served as a benchmark model for which full sets of temporal data and building information were used as inputs. The recurrent neural network models were trained and tested assuming various available types and amounts of temporal data and known building physical information to investigate the effects of data and information availability. Feature importance analysis was conducted to select the key variables for different prediction targets under different scenarios. This research provides guidance in selecting an appropriate building thermal response modeling method based on the measured data availability, building physical information, and application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Effects of short-term over-discharge cycling on the performance of commercial 21,700 lithium-ion cells and the identification of degradation modes

In this paper, short-term over-discharge cycling was performed on commercially available 21,700 lithium-ion cells to investigate its effects on cell performance; the degradation modes were also identified and analyzed in detail using both in-situ and ex-situ methods. Results show that observable capacity loss occurs when the cell is over-discharged to 112.5% depth of discharge. Moreover, the negative impact of the depth of discharge on cell performance (or cell aging) is more serious than the number of cycles, and continuous over-discharge cycling will accumulate such impact. The loss of Li inventory related to the decomposition and reformation of solid electrolyte interphase film is an important cause of the irreversible capacity loss/degradation of Li-ion cells during over-discharge cycling testing. Furthermore, the dissolution of copper current collector can greatly reduce the mechanical stability of the anode, and further, the deposition of Cu, the exfoliation and the cracking of active material particles can influence the transfer of ions and lead to the loss of Li inventory and the loss of active material within Li-ion cells. Additionally, when the depth of discharge exceeds 108.3%, deposition of Cu is observed on the ceramic-covered side of separators.

25 ENERGY STORAGE↗
DOE OSTI2024

Approach to startup inventory for viable commercial fusion power plant

With the increasing efforts to commercialize fusion power, private and government organizations are investing heavily in the development of technology to support a viable fusion power plant. Deuterium-Tritium (DT) fueled reactors are more prevalent than other proposed designs, requiring tritium processing and handling technology for safe operations and self-sufficiency. Further, each fusion power plant will need a specific-to-design startup inventory of tritium to begin operations. This startup inventory is required prior to breeding and is the minimum tritium inventory required to fill each processing component in the fuel cycle, to offset radioactive decay losses, and to avoid a zero-fuel situation for continuous operation. We present an approach to calculate the startup tritium inventory for a 500 MW th reactor, with considerations for reserve inventory for maintenance and commissioning. A baseline startup inventory was calculated to be approximately 327 gs. This value was obtained using modest assumptions about the technology and operating parameters of a fusion power plant. The required operating reserve inventory or the inventory necessary to keep a fusion power plant operational using only direct internal recycling for 24 h for the same plant design is approximately 642 gs. The approach and findings of this paper will enable fusion energy stakeholders to better utilize the existing scarce global tritium supply.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A deep learning-accelerated data assimilation and forecasting workflow for commercial-scale geologic carbon storage

Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO 2 ) plume migration under geologic uncertainties is a challenging problem in geologic carbon storage. The high computational cost of data assimilation with a high-dimensional parameter space impedes fast decision-making for commercial-scale reservoir management. We propose to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow. Applying an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates geologic properties and predicts reservoir performance with quantified uncertainty from pressure history and CO 2 plumes interpreted through seismic inversion. As the most computationally expensive component in such a workflow is reservoir simulation, we developed surrogate models to predict dynamic pressure and CO 2 plume extents under multi-well injection. The surrogate models employ deep convolutional neural networks, specifically, a wide residual network and a residual U-Net. The workflow is validated against a flat threedimensional reservoir model representative of a clastic shelf depositional environment. Intelligent treatments are applied to bridge between quantities in a true-3D reservoir model and those in a single-layer reservoir model. The workflow can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

25 ENERGY STORAGE↗
DOE OSTI2024

Gigaton commercial-scale carbon storage and mineralization potential in stacked Columbia River basalt reservoirs

This work presents a detailed supercritical CO 2 storage resource estimation for the stacked basalt reservoirs in the Grande Ronde Basalt of the Columbia River Basalt Group in eastern Washington and Oregon. The assessment aims to derisk the commercialization potential of geologic carbon storage in basalt by leveraging both structural and mineralization trapping of CO 2 in basalt. The structural closures formed by anticlinal ridges and synclinal valleys in Yakima Fold Belt are excellent physical traps to accommodate injected supercritical CO 2 . Rigorous hydraulic testing, well logs and simulation results from the Wallula Basalt Pilot #1 well showed the occurrence of 17 suitable permeable injection zones (up to 2,496 mD) intercalated with dense seals (~2.6E-10 mD) in the Grand Ronde Basalt. In addition, geochemical studies showed fast reactions between supercritical CO 2 and dissolved basalt minerals to form stable carbonates. In conclusion, our calculation indicates up to 40 gigatons (P90) of mineralization storage resources exist in the Grande Ronde Basalt reservoirs.

58 GEOSCIENCES↗
DOE OSTI2022

Dual-scale folding in cutting of commercially pure aluminum alloys

We examine a, hitherto, little-studied and curious machining chip morphology, with tell-tale signs of folding at two different length scales, that is common in cutting of certain ductile and highly strain-hardening metals like soft aluminum alloys, tantalum and niobium. This chip morphology does not appear in the usual catalogues of common chip types. The mechanics of formation of the “dual-scale folded chip” is studied in model material systems of commercially pure aluminum alloys (AA 1100 and AA 8040), that prominently exhibit this chip morphology. The flow, folding and associated plastic instabilities are investigated using micro/macro structure observations of the chip in a plane-strain cutting framework, with high-speed in situ imaging and image analysis of material flow; and force measurements. The smaller-scale folding is shown to develop in the primary deformation zone while the larger-scale folding occurs as the chip traverses the rake face of the tool. The resulting chip is composed of irregularly-spaced large folds, superimposed onto which are the quasi periodic small folds. The representative wavelengths of the two folds differ on average by an order of magnitude, 0.1 mm vs. 2 mm. The observations reveal a direct coupling between the material flow and chip morphology, and how specific attributes of the dual-scale folded chip arise from the flow mechanism. Plastic buckling is found to play a key role in the folding at both length scales. The small-scale folds are characteristic of a sinuous plastic flow mode, while the large-scale folding is characterized by buckling and stick-slip along the tool rake face, triggered by adhesive pinning of the chip to the tool. Important consequences of the dualscale folding are very large cutting forces, and force oscillations of large amplitude, despite the alloys being very soft, only ~ 25 HV. Here, the dual-scale folding is why many of these alloys are classified as “gummy” to machine. Since the dual-scale folded chip is associated with large cutting forces and poor surface quality, there is much to be gained by disrupting this flow type in practical machining applications. Methods for controlling the folding to improve machining performance with the gummy alloys are briefly discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Characterization of modeling and experimental data inconsistencies from burst testing for high-burnup commercial fuel rod applications

Fuel fragmentation, relocation, and dispersal are some of the largest issues remaining in the nuclear industry before rod-average burnup can be increased beyond 62 GWd/tU. The issue is primarily related to the potential for fuel to be dispersed into the reactor primary system, which may increase public risk. One way to prevent dispersal is to avoid cladding burst. The objective of this work is to support the high burnup safety case by evaluating cladding burst under high-burnup, full-length fuel rods and to identify uncertainties that could improve model predictions. The results of this analysis will evaluate realistic, prototypic loss-of-coolant accident (LOCA) conditions; support future cladding burst test designs; and inform the development of mechanistic material models. Realistic high-burnup operating conditions were implemented in the BISON fuel performance code to simulate steady-state and LOCA transient fuel rod evolution to the point at which cladding burst occurred. Parametric studies are performed to assess code response to changes in rod internal pressures and heating rates. Results were compared with simulated LOCA experiments to identify inconsistencies between commercial fuel rod analysis and experimental validation. The representative full-length fuel rod LOCA simulation results did not agree with cladding burst tests. Cladding burst tests indicated burst occurring well below (100–150 °C) those calculated in the full-length fuel rod LOCA analysis. Further investigation indicated that the cladding burst tests do not appear to be representative for full-length fuel rods. The inconsistency investigated in this work showed that the differences between the BISON simulation and the experiment's cladding burst conditions arise from an incomplete characterization of the cladding surface temperature, detailed rodlet characterization, lack of cladding strain measurements, and uncertainty in the cladding creep and failure models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Natural isotopic compositions of titanium, iron, and nickel observed in commercial fuel pellets – Promising candidate elements for stable isotope tagging

Stable isotope taggants would constitute unique identifiers for nuclear fuel cycle materials, resulting in expedited timelines and high confidence provenance assessments for nuclear forensics investigations. However, reliably identifying and interpreting stable isotope taggants in nuclear materials recovered from outside of regulatory control will largely be predicated on the assumption that the taggant element intrinsic to the untagged nuclear material exhibits natural isotopic ratios. Here, we present high-precision Ti, Fe, and Ni isotope compositions in 13 commercial low-enriched uranium (LEU) fuel pellets to assess the suitability of these transition metals as stable isotope taggants. Our investigations reveal limited isotope variations among the fuel pellets in all three elements, which are consistent with small mass-dependent isotope fractionations, comparable to variations previously reported for natural samples. In practice, isotopically tagged nuclear materials are expected to fall along isotopic mixing lines, since intrinsic background levels of taggant elements dilute the taggant towards natural isotope compositions. Furthermore, the observation that Ti, Fe, and Ni isotope compositions in a suite of LEU fuel pellets are close to or indistinguishable from estimates for the Bulk Silicate Earth demonstrates that a two end-member mixing assumption would be valid for these transition metals, indicating that all three are promising candidate elements for stable isotope tagging. Finally, we present mass balance calculations to quantify isotopic perturbations expected from admixing isotopically anomalous Ti, Fe, and Ni taggants to assess the interplay between elemental and taggant concentrations and find favorable compromises for facilitating successful taggant identification with current analytical methods.

Intentional forensics↗