Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “MITIGATION”

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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Advances in Carbon Capture and Use (CCU) Technologies: A Comprehensive Review and CO2 Mitigation Potential Analysis

One of society’s major current challenges is carbon dioxide emissions and their consequences. In this context, new technologies for carbon dioxide (CO2) capture have attracted much attention. One of these is carbon capture and utilization (CCU). This work focuses on the latest trends in a holistic approach to carbon dioxide capture and utilization. Absorption, adsorption, membranes, and chemical looping are considered for CO2 capture. Each CO2 capture technology is described, and its benefits and drawbacks are discussed. For the use of carbon dioxide, various possible applications of CCU are described, starting with the utilization of carbon dioxide in agriculture and proceeding to the conversion of CO2 into fuels (catalytic processes), chemicals (photocatalytic processes), polymers, and building supplies. For decades, carbon dioxide has been used in industrial processes, such as CO2-enhanced oil recovery, the food industry, organic compound production (such as urea), water treatment, and, therefore, the production of flame retardants and coolants. There also are several new CO2-utilization technologies at various stages of development and exploitation, such as electrochemical conversion to fuels, CO2-enhanced oil recovery, and supercritical CO2. At the end of this review, future opportunities are discussed regarding machine learning (ML) and life cycle assessment (LCA).

Peres, Christiano B.↗
DOE OSTI2021

A Survey on Cybersecurity Challenges, Detection, and Mitigation Techniques for the Smart Grid

The world is transitioning from the conventional grid to the smart grid at a rapid pace. Innovation always comes with some flaws; such is the case with a smart grid. One of the major challenges in the smart grid is to protect it from potential cyberattacks. There are millions of sensors continuously sending and receiving data packets over the network, so managing such a gigantic network is the biggest challenge. Any cyberattack can damage the key elements, confidentiality, integrity, and availability of the smart grid. The overall smart grid network is comprised of customers accessing the network, communication network of the smart devices and sensors, and the people managing the network (decision makers); all three of these levels are vulnerable to cyberattacks. In this survey, we explore various threats and vulnerabilities that can affect the key elements of cybersecurity in the smart grid network and then present the security measures to avert those threats and vulnerabilities at three different levels. In addition to that, we suggest techniques to minimize the chances of cyberattack at all three levels.

Tufail, Shahid↗
DOE OSTI2022

Forced Oscillation Grid Vulnerability Analysis and Mitigation Using Inverter-Based Resources: Texas Grid Case Study

Forced oscillation events have become a challenging problem with the increasing penetration of renewable and other inverter-based resources (IBRs), especially when the forced oscillation frequency coincides with the dominant natural oscillation frequency. A severe forced oscillation event can deteriorate power system dynamic stability, damage equipment, and limit power transfer capability. This paper proposes a two-dimension scanning forced oscillation grid vulnerability analysis method to identify areas/zones in the system that are critical to forced oscillation. These critical areas/zones can be further considered as effective actuator locations for the deployment of forced oscillation damping controllers. Additionally, active power modulation control through IBRs is also proposed to reduce the forced oscillation impact on the entire grid. The proposed methods are demonstrated through a case study on a synthetic Texas power system model. The simulation results demonstrate that the critical areas/zones of forced oscillation are related to the areas that highly participate in the natural oscillations and the proposed oscillation damping controller through IBRs can effectively reduce the forced oscillation impact in the entire system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Bio-Based Polyisoprene Can Mitigate Climate Change and Deforestation in Expanding Rubber Production

Biomass is a promising renewable feedstock to produce polyisoprene for the rubber industry. Through metabolic engineering, sugars derived from pretreated and hydrolyzed cellulose and hemicellulose can be directly fermented to isoprene to produce rubber. Here we investigate the life cycle environmental impact of isoprene fermentation to produce bio-polyisoprene from agricultural residues (of Zea mays L.). Results show that the greenhouse gas (GHG) intensity of bio-polyisoprene (−4.59 kg CO2e kg−1) is significantly lower than that of natural rubber (Hevea brasiliensis) and synthetic rubber (−0.79 and 2.41 kg CO2e kg−1, respectively), while supporting a circular biogenic carbon economy. We found the land use intensity of bio-polyisoprene to be 0.25 ha metric ton−1, which is 84% lower than that from rubber tree plantations. We compare the direct fermentation to isoprene results with indirect fermentation to isoprene through the intermediate, methyl butyl ether, where dehydration to isoprene is required. The direct fermentation of isoprene reduces reaction steps and unit operations, an expected outcome when employing process intensification, but our results show additional energy conservation and reduced contribution to climate change. Among the ReCiPe life cycle environmental impact metrics evaluated, air emission related impacts are high for bio-polyisoprene compared to those for natural and synthetic rubber. Those impacts can be reduced with air emission controls during production. All other metrics showed an improvement for bio-polyisoprene compared to natural and synthetic rubber.

Batten, Rahamim↗
DOE OSTI2025

Evaluating the Effectiveness of Soil Profile Rehabilitation for Pluvial Flood Mitigation Through Two-Dimensional Hydrodynamic Modeling

Pluvial flooding, driven by increasingly impervious surfaces and intense storm events, presents a growing challenge for urban areas worldwide. In Baltimore City, MD, USA, climate change, rapid urbanization, and aging stormwater infrastructure are exacerbating flooding impacts, resulting in significant socio-economic consequences. This study evaluated the effectiveness of a soil profile rehabilitation scenario using a 2D hydrodynamic modeling approach for the Tiffany Run watershed, Baltimore City. This study utilized different extreme storm events, a high-resolution (1 m) LiDAR Digital Terrain Model (DTM), building footprints, and hydrological soil data. These datasets were integrated into a fully coupled 2D hydrodynamic model, the City Catchment Analysis Tool (CityCAT), to simulate urban flood dynamics. The pre-soil rehabilitation simulation revealed a maximum water depth of 3.00 m in most areas, with hydrologic soil groups C and D, especially downstream of the study area. The post-soil rehabilitation simulation was targeted at vacant lots and public parcels, accounting for 33.20% of the total area of the watershed. This resulted in a reduced water depth of 2.50 m. Additionally, the baseline runoff coefficient of 0.49 decreased to 0.47 following the rehabilitation, and the model consistently recorded a peak runoff reduction rate of 4.10 across varying rainfall intensities. The validation using a contingency matrix demonstrated true-positive rates of 0.75, 0.50, 0.64, and 0 for the selected events, confirming the model’s capability at capturing real-world flood occurrences.

Baltimore City↗
DOE OSTI2020

Mitigating Scatter in Mechanical Properties in AISI 410 Fabricated via Arc-Based Additive Manufacturing Process

Wire-based metal additive manufacturing utilizes the ability of additive manufacturing to fabricate complex geometries with high deposition rates (above 7 kg/h), thus finding applications in the fabrication of large-scale components, such as stamping dies. Traditionally, the workhorse materials for stamping dies have been martensitic steels. However, the complex thermal gyrations induced during additive manufacturing can cause the evolution of an inhomogeneous microstructure, which leads to a significant scatter in the mechanical properties, especially the toughness. Therefore, to understand these phenomena, arc-based additive AISI 410 samples were fabricated using robotic gas metal arc welding (GMAW) and were subjected to a detailed characterization campaign. The results show significant scatter in the tensile properties as well as Charpy V-notch impact toughness data, which was then correlated to the microstructural heterogeneity and delta (δ) ferrite formation. Post-processing (austenitizing and tempering) treatments were developed and an ~70% reduction in the scatter of tensile data and a four-times improvement in the toughness were obtained. The changes in mechanical properties were rationalized based on the microstructure evolution during additive manufacturing. Based on these, an outline to tailor the composition of “printable” steels for tooling with isotropic and uniform mechanical properties is presented and discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mitigation of Cu-Induced Grain Boundary Sensitization in Steel Wire Rods Through a Desensitization Heat Treatment

Steel wire rods are essential for manufacturing high-strength steel tire cords. Yet, the presence of residual copper (Cu) in recycled steel can cause grain-boundary sensitization, embrittlement, and deterioration of the mechanical performance of the final product. This study introduces a desensitization heat treatment step designed to redistribute Cu away from austenite grain boundaries after sensitization occurs. The treatment consists of a 10 min dwell at 1000 °C in a 5%H 2 -Ar reducing atmosphere followed by quench. The temperature and hold time were selected based on diffusion calculations to promote solid-state back diffusion of Cu without altering grain morphology. Experimental validation showed that the dwell step reduced the length of Cu-rich sensitized zones of steel wire rod samples containing 0.21 wt.% Cu by approximately 89% and restored the mechanical properties to nearly 95–98% relative to low-Cu baseline steel (0.01 wt.% Cu). Compared with sensitized and as-obtained samples, these results highlight the effectiveness of the proposed method in improving both the microstructure and tensile performance of recycled steel wire rods, enabling their potential application in tire manufacturing.

copper↗
DOE OSTI2020

Modeling Green Roof Potential to Mitigate Urban Flooding in a Chinese City

The Middle and Lower Reaches of the Yangtze River (MLRYR) region, which has humid subtropical climate conditions and unique plum rain season, is characterized by a simultaneous high-frequency urban flooding and reduction in groundwater levels. Retrofitting the existing buildings into green roofs is a promising approach to combat urban flooding, especially for a densely developed city. Here, the application potential of the Green Roof System (GRS) and the Improved Green Roof System (IGRS) designed to divert overflowing water from green roofs to recharge groundwater were analyzed in a densely developed city, Nanchang, China. For the first time, the influence of GRS on the hydraulic condition of Combined Sewage System/Storm Water System (CSS/SWS) is analyzed, which is a direct reflection of the effect of GRS on alleviating urban flooding. The simulation results show that GRS can retain about 41–75% of precipitation in a 2-hour timescale and the flooding volumes in the GRS/IGRS region are 82% and 28% less than those of the Traditional Roof System (TRS) in 10- and 100-yr precipitation events, respectively. In the continuous simulations, GRS also enhances Evapotranspiration (ET), which accounts for 39% of annual precipitation, so that reduces the cumulative surface runoff. Considering the IGRS can provide more hydrological benefits than the GRS under the same climate conditions, we may conclude that the widespread implementation of both the GRS and the IGRS in Nanchang and other densely developed cities in the MLRYR region could significantly reduce surface and peak runoff rates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Advancing How We Learn from Biodesign to Mitigate Risks with Next-Generation Genome Engineering

In the last decade, the unprecedented simplicity and flexibility of the CRISPR-Cas system has made it the dominant transformative tool in gene and genome editing. However, this democratized technology is both a boon and a bane, for which we have yet to understand the full potential to investigate and rewrite genomes (also named “genome biodesign”). Rapid CRISPR advances in a range of applications in basic research, agriculture, and clinical applications pose new risks and raise several biosecurity concerns. In such a fast-moving field of research, we emphasize the importance of properly communicating the quality and accuracy of results and recommend new reporting requirements for results derived from next-generation genome engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Mitigating Shear-dependent Object Detection Biases with Metacalibration

M ETACALIBRATION is a new technique for measuring weak gravitational lensing shear that is unbiased for isolated galaxy images. Here we test M ETACALIBRATION with overlapping, or "blended" galaxy images. Using standard M ETACALIBRATION , we find a few percent shear measurement bias for galaxy densities relevant for current surveys, and that this bias increases with increasing galaxy number density. We show that this bias is not due to blending itself, but rather to shear-dependent object detection. If object detection is shear-independent, no deblending of images is needed, in principle. We demonstrate that detection biases are accurately removed when including object detection in the M ETACALIBRATION process, a technique we call M ETADETECTION . This process involves applying an artificial shear to images of small regions of sky and performing detection on the sheared images, as well as measurements that are used to calculate a shear response. We demonstrate that the method can accurately recover weak shear signals even in highly blended scenes. In the M ETACALIBRATION process, the space between objects is sheared coherently, which does not perfectly match the real universe in which some, but not all, galaxy images are sheared coherently. We find that even for the worst case scenario, in which the space between objects is completely unsheared, the resulting shear bias is at most a few tenths of a percent for future surveys. We discuss additional technical challenges that must be met in order to implement M ETADETECTION for real surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Mitigating CO 2 Corrosion of Natural Gas Steel Pipelines by Thermal Spray Aluminum Coatings

We report internal pipeline corrosion due to carbon dioxide (CO 2 ) is a major challenge facing the oil and gas industry. The objective of this study was to investigate the corrosion behavior of aluminum (Al)-based alloys as sacrificial coatings to protect pipelines in a CO 2 -saturated aqueous electrolyte (3.5 wt% NaCl) at 4 bar CO 2 partial pressure (3 bar) and 40°C. The corrosion resistance of Al-based alloys and thermal spray coatings was evaluated in an electrochemical reaction autoclave using electrochemical methods (potentiodynamic polarization, linear polarization resistance, and electrochemical impedance spectroscopy). Post-corrosion surface characterization was performed by scanning electron microscopy equipped with energy-dispersive x-ray spectroscopy. The obtained data show Al-based alloys demonstrated promising protection against CO 2 corrosion with no breakaway degradation issues.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mechanisms of Mitigating Chloride-Induced Stress Corrosion Cracking of Austenitic Steels by Laser Shock Peening

This study investigates the effect of laser shock peening (LSP) on the chloride-induced stress corrosion cracking (SCC) of 304 austenitic steels. LSP can induce a high compressive residual stress to a depth of 700 µm and plastic deformation structures of dislocations, deformation twins, and stacking faults. Constant-load SCC tests in MgCl2 solution suggested that LSP can retard the crack initiation and slow the crack growth. LSP-treated subsurface layers experience ductile fracture while the central regions exhibit intergranular SCC. The LSP-induced deformation structures may impede dislocation slips, while the LSP-induced compressive residual stress can lessen the stress intensity factor of crack tips and decrease the local stress for film rupture.

Materials Science↗
DOE OSTI2023

Design of a Continuous Electrochemical Purification Reactor for Corrosion Mitigation in Molten Chloride Salt Systems

The utility of molten chloride salts in concentrating solar power (CSP) is dependent on the ability to maintain low corrosive impurities. Without proper purification, the corrosion rates of containment alloys exceed the industry standard of corrosion—under 20 μm/year. An extensive body of literature focuses on the initial purification stage of molten chloride salts. However, occurrences such as maintenance, leaks, and so forth expose the salt to the atmosphere and reintroduce impurities. Therefore, it is critical to develop a purification strategy that can control impurity levels during CSP plant operation. Here we present the design and fabrication of a purification vessel to continuously remove impurities out of flowing molten salt.

Witteman, Liam↗
DOE OSTI2025

Mitigating Impact Through Community-Engaged Flood Modeling

Urban pluvial flooding poses a growing threat to the city of Baltimore, driven by heavy rainfall, increased impervious area, and aging infrastructure. Adapting to the risks posed by pluvial flooding is critical for building greater climate resiliency in Baltimore's Inner Harbor Watershed. This study addresses these challenges through community-informed decision analysis, which uses hydrologic modeling and optimization tools to identify robust flooding adaptation pathways. We will collaborate with community partners to identify key concerns and objectives regarding flooding. These concerns have been purposefully built in to a combined surface-subsurface dynamic flow simulation model. Model outputs are used to identify flooding locations within the Inner Harbor, and to test adaptation methods. Machine learning will be used search for solutions which meet diverse environmental, financial, and social goals, and solution performance will be examined under a wide range of potential future climatic conditions and integrated with an adaptive planning approach. This novel set of adaptation pathways will enhance the City's capacity to respond to evolving pluvial flood risk.

climate resilience↗
DOE OSTI2025

Community-Informed Urban Flood Modeling for Impact Mitigation

The intensification of the hydrologic cycle due to climate change poses a threat to aging and under-designed water infrastructure systems which cannot adequately manage intense storm events. Developing a comprehensive plan for managing rain-driven flooding events is challenging due to uncertainties in the magnitude and frequency of future storm events and conflicting stakeholder objectives. In the City of Baltimore, Maryland, stormwater infrastructure is struggling to keep up with rainfall-driven (pluvial) flooding events, which regularly damage housing and disrupt transportation for residents. In this study, a hybrid of community engagement, numerical modeling, and artificial intelligence techniques are employed to explore prospective urban flooding adaptations. Community engagement drives the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed. The model integrates complex surface and subsurface stormwater infrastructure data from the City, high-resolution spatial data, insights from local public works experts, and the lived experiences of City residents. This co-developed model simulates adaptations of interest to stakeholders in the city, including green and grey infrastructure and operational management strategies. Stormwater management scenarios focused on inlet cleaning and spatially concentrated green infrastructure are found to be the most effective in reducing flood depths in community priority locations. Together, these adaptations can reduce the duration of intersection inundation by more than twenty minutes, allowing for quicker emergency response and restoration of typical transportation systems. Future work will combine this community engaged flooding model with the Deep Uncertainties Pathways framework to explore tradeoffs between adaptations and develop dynamic adaptations which align with community objectives, enhance climate resilience in Baltimore, and can be adjusted in response to changing future conditions.

Ava, Spangler [Pennsylvania State University]↗
DOE OSTI2026

Community-Informed Urban Flood Modeling for Impact Mitigation

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Baltimore MD↗