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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pilot testing of CO2 capture from a coal-fired power plant—Part 2: Results from 1-MWe pilot tests

Abstract Using a 1-MWe slipstream pilot plant, solid-sorbent-based post-combustion CO2 capture was tested at a coal-fired power plant. Results from pilot testing were used to develop a preliminary full-scale commercial design. The sorbent selected for pilot-scale evaluation during this project consisted of an ion-exchange resin that incorporated amines covalently bonded to the substrate. A unique temperature-swing-absorption (TSA) process was developed that incorporated a three-stage fluidized-bed adsorber integrated with a single-stage fluidized-bed regenerator. Overall, following start-up and commissioning challenges that are often associated with first-of-a-kind pilots, the pilot plant operated as designed and expected, with a few key exceptions. The two primary exceptions were associated with: (i) handling characteristics of the sorbent, which were sufficiently different at operating temperature than at ambient temperature when design specifications were established with lab-scale testing; and (ii) CO2 adsorption in the transport line between the regenerator and adsorber that preloaded the sorbent with CO2 prior to entering the adsorber. Results from the pilot programme demonstrate that solid-sorbent-based post-combustion capture can be utilized to achieve 90% CO2 capture from coal-fired power plants.

Sjostrom, Sharon↗
DOE OSTI2022

Real-time streaming tomographic reconstruction with on-demand data capturing and 3D zooming to regions of interest

Complex dynamic tomographic experiments at brilliant X-ray light sources require real-time feedback on the sample changes with respect to environmental conditions, selecting representative regions of interest for high-resolution scanning, and on-demand data saving mechanisms for storing only relevant projections acquired by fast area detectors and reducing data volumes. Here the implementation details of a 3D real-time imaging monitoring instrument, with zooming to a volume of interest with easy-to-use visualization via ImageJ , a tool familiar to most beamline users, is presented. The instrument relies on optimized data flow between the detector and processing machines and is implemented on commodity computers. The instrument has been developed at beamline 2-BM of the Advanced Photon Source, where the automatic lens changing mechanism for zooming is implemented with an Optique Peter microscope. Performance tests demonstrate the ability to process more than 3 GB of projection data per second and generate real-time 3D zooming with different magnification. These new capabilities are essential for new APS Upgrade instruments such as the projection microscope under development at beamline 32-ID. The efficacy of the proposed instrument was demonstrated during an in situ tomographic experiment on ice and gas hydrate formation in porous samples.

3D zooming↗
DOE OSTI2026

Numerical Modeling of a Two-Stage Ocean Current Turbine

The Equinox Ocean Turbines (EQOT) current energy converter has a unique design with power generation in two small-diameter turbines attached to the tips of a large-diameter passive rotor. This configuration offers some key advantages for capturing ocean currents. With no centrally placed generator, almost no reaction torque is required at the nacelle of the main large-diameter rotor, and the small-diameter tip turbine generators operate at a higher speed and lower torque. The physics that determine the performance and loads on the turbine are also unique. The interactions of the flow field between the two stages and the general architecture of the system cannot be captured with traditional mid-fidelity modeling tools. For design iterations and large sets of load cases, it is important to have mid-fidelity models that can capture the important phenomenon with enough accuracy to identify global trends. This work uses a limited set of high-fidelity computational fluid dynamics (CFD) simulations to help inform the selection of and construction of a custom mid-fidelity model. Mid-fidelity modeling approaches were verified by comparing key turbine performance quantities to those found with the CFD model. Hydrodynamic interactions of the two-stage rotor were identified through high-fidelity CFD modeling. This highlighted the impact of the main rotor tip vortex and wake on the secondary rotor apparent inflow. This results in a relative flow rotation and sharp deficit, that change the optimal secondary rotor rotation speed and adds unsteadiness to the blade loading respectively. Multiple mid-fidelity approaches were evaluated for their ability to capture these effects. A simple approximation of the combined-stage performance based on single-stage BEM provides a reasonable rough prediction, especially near the peak TSR values, with some larger discrepancy at higher TSRs. Predicting the combined-stage performance based on single-stage CFD data improves this prediction across the TSR range. Although the combined-stage modeling in OLAF was not successful in this stage of the project, it showed promise as a mid-fidelity method, assuming the parameters can be tuned to account for the significant differences in time and length scales between the main and secondary rotors. This may be addressed through code changes in future work. A significant finding from the OLAF work was the agreement between the vortex core radius values found independently via a parameter space search and via CFD. The technique of using single-stage secondary rotor BEM, with a custom inflow taken from single-stage main rotor CFD or OLAF, provides an efficient method to capture one-way coupled flow interactions. This method provided generally good predictions of the impact of the flow rotation on the secondary rotor but struggled to accurately predict the peaks of the unsteady load progression. Future work could include some superposition of a tuned main rotor trailing edge viscous wake into the custom inflow to better predict this interaction.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Implementation of Genetic Algorithms to Optimize Metal–Organic Frameworks for CO 2 Capture

Metal-organic frameworks (MOFs) are promising materials for CO 2 capture with the potential to use less energy than current industrial CO 2 capture methods. MOFs are highly versatile sorbents, and there is an almost unlimited number of MOFs that could be synthesized. In this work, we used a genetic algorithm (GA) and grand canonical Monte Carlo (GCMC) simulations to efficiently search for high-performing MOFs for CO 2 capture. We analyzed the effects of important GA parameters, including the mutation probability, the number of MOFs per generation and the number of GA generations, on the GA performance. Here, we performed GCMC simulations on-the-fly during the GA procedure to determine the performance of proposed MOFs and optimized their structures using multiple objective functions across different topologies. The GA was able to determine top-performing MOFs balancing CO 2 selectivity versus working capacity and reduced the cost of molecular simulations by a factor of 25 versus brute-force screening of an entire database of structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Microwave-Assisted Reactive CO 2 Capture with the SrCO 3 -Graphite System

This study details the initial development of a microwave heat-driven reactive CO 2 capture (RCC) process using the SrO/SrCO 3 cycle and graphitic carbon to absorb ppm-levels of CO 2 from humidified room temperature air and selectively convert it into CO. By combining first-principles density functional theory (DFT) simulations with thermogravimetric analysis (TGA) and X-ray diffraction (XRD) verification, it is demonstrated that SrO spontaneously absorbs moisture to generate Sr(OH) 2 followed by Sr(OH) 2 *1H 2 O, which then can spontaneously react with atmospheric levels of CO 2 to form SrCO 3 . The resulting SrCO 3 can then react with solid carbon at elevated temperatures to selectively produce CO and regenerate SrO. Graphitic carbon is an excellent microwave absorber that can quickly generate temperatures approaching 1000 °C and then cool to room temperature within minutes, potentially allowing for integration with intermittent electricity. It is shown that using microwaves to selectively heat a mixture of graphitic carbon and SrCO 3 produced CO with 85 ± 3% selectivity and stable performance over ten cycles. The rapid heating for release and room temperature CO 2 uptake processes appeared to prevent performance loss from particle sintering typically observed with traditional thermal systems. In conclusion, these results demonstrate a new RCC approach that adds to the growing number of potential technologies available for converting CO 2 to useful chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Porosity as a Design Element for Developing Catalytic Molecular Materials for Electrochemical and Photochemical Carbon Dioxide Reduction

The catalytic reduction of carbon dioxide (CO 2 ) using sustainable energy inputs is a promising strategy for upcycling of atmospheric carbon into value-added chemical products. This goal has inspired the development of catalysts for selective and efficient CO 2 conversion using electrochemical and photochemical methods. Among the diverse array of catalyst systems designed for this purpose, two- and three-dimensional platforms that feature porosity offer the potential to combine carbon capture and conversion. Included are covalent organic frameworks (COFs), metal-organic frameworks (MOFs), porous molecular cages, and other hybrid molecular materials developed to increase active site exposure, stability, and water compatibility while maintaining precise molecular tunability. This mini-review showcases catalysts for the CO 2 reduction reaction (CO 2 RR) that incorporate well-defined molecular elements integrated into porous materials structures. Selected examples provide insights into how different approaches to this overall design strategy can augment their electrocatalytic and/or photocatalytic CO 2 reduction activity. This article is protected by copyright. All rights reserved.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Molecular-level solvation and selectivity behavior of Na + , K + , and Li + within glycerol-derived solvents

Ether-based acyclic solvents have a tendency to confine positively charged atoms, forming structures called podands. Due to the stability of these structures, podands have been identified as promising candidates for several different electrochemical applications. In this work, we use molecular dynamics simulations to investigate the solvation and selectivity of Na + , K + , and Li + by different glycerol-derived solvents. The structural properties suggest that the solvent-cation association is stable over a very wide temperature range. Further, a strong correlation is observed between the more electronegative oxygen sites and preferential interaction with the cations, which suggests that the electrostatic oxygen-ion interactions dominate the coordination between these species. Significantly more intense interactions are observed between the solvents and Li + , versus Na + or K + . These molecular-level thermodynamic insights provide fundamental support for further exploring the performance of glycerol-derived podand complexes in Li + capture applications and/or electrolyte formulations.

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

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗
DOE OSTI2022

Matrimid substrates with bicontinuous surface and macrovoids in the bulk: A nearly ideal substrate for composite membranes in CO 2 capture

Scalable fabrication of thin-film composite (TFC) membrane for post-combustion carbon capture is often limited by the availability of high-performance nanoporous substrate. Ideally, the substrate should allow for fast gas transport at the selective layer/substrate interface as well as in the bulk of the substrate. In this study, highly permeable Matrimid substrates were prepared via vapor- and nonsolvent-induced phase separations. The phase separation mechanism of the Matrimid®/N-methyl-2-pyrrolidone casting solution was modulated by the addition of LiCl to control the solution thermodynamic stability, and nanoporous Matrimid substrates were formed with a bicontinuous surface and macrovoids in the bulk. This hierarchically optimized structure resulted in a CO 2 permeance of 2.60 × 10 5 GPU (1 GPU = 1 × 10 –6 cm 3 (STP) cm –2 s –1 cmHg –1 = 3.349 × 10 –10 mol m –2 s –1 Pa –1 ), which was ca. 11 times more permeable than a benchmark polyethersulfone substrate with cellular pores. The benefit of using this new substrate was demonstrated by coating a 170-nm amine-containing polymer to form a TFC facilitated transport membrane. The membrane exhibited a CO 2 permeance of 932 GPU at 57°C, which was 72 GPU higher than the counterpart coated on the benchmark substrate. Meanwhile, the CO 2 /N 2 selectivity was remained at 158. This permeance improvement could be well explained by the resistance-in-series model, where the improved permeance was attributed to the reductions in substrate and lateral diffusion mass transfer resistances. The upper bound (UB) analysis indicates that the Matrimid substrate is nearly ideal for the state-of-the-art polymers for CO 2 /N 2 separation. Here, the substrate improvement could also reduce the parasitic energy associated with the membrane process due to the reduced membrane cost and flue gas compression requirement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2026

Ultrafast x-ray imaging of coherently controlled molecular dynamics in real space and time

Coherent control aims to manipulate chemical processes on the latent length and timescales of atoms and bonds, scales that are intrinsic to molecular dynamics but not directly resolved by most experimental probes. As a result, existing coherent-control experiments, which overwhelmingly rely on spectroscopic observables, leave a crucial blind spot: the direct, real-space recovery of all atomic and molecular rearrangements in response to coherently controlled excitations. Here, we overcome this limitation by integrating a Tannor-Kosloff-Rice pump-control-probe scheme with ultrafast X-ray scattering to capture snapshots of the wavepacket motion in a benchmark molecular system. We demonstrate this by photoexciting diatomic iodine vapor with a visible pump pulse, selectively steering the wavepacket toward ground-state recombination or dissociative pathways with a time-delayed near-IR control pulse, and recording the dynamics with angstrom and femtosecond precision with an ultrashort hard X-ray probe pulse. By comparing these structural observations with numerical solutions of the time-dependent Schrödinger equation, we reveal how coherent control actively reshapes the molecular charge density distribution. Our results pave the way for leveraging structural feedback as a control handle and provide a fundamental microscopic visualization of quantum decoherence and energy redistribution at the atomic level.

Hopper, Thomas R. [SLAC National Accelerator Labor↗
DOE OSTI2025

Hyperselective carbon membranes for precise high-temperature H 2 and CO 2 separation

More than 90% of the world’s hydrogen (H 2 ) is produced from fossil fuel sources, which requires energy-intensive separation and purification to produce high-purity H 2 fuel and to capture the carbon dioxide (CO 2 ) by-product. While membranes can decarbonize H 2 /CO 2 separation, their moderate H 2 /CO 2 selectivity requires secondary H 2 purification by pressure swing adsorption. Here, we report hyperselective carbon molecular sieve hollow fiber membranes showing H 2 /CO 2 selectivity exceeding 7000 under mixture permeation at 150°C, which is almost 30 times higher than the most selective nonmetallic membrane reported in the literature. The membrane is able to maintain an ultrahigh H 2 /CO 2 selectivity over 1400 under mixture permeation at 400°C. Pore structure characterization suggests that highly refined ultramicropores are responsible for effectively discriminating the closely sized H 2 and CO 2 molecules in the hyperselective carbon molecular sieve membrane. Modeling shows that the unprecedented H 2 /CO 2 selectivity will potentially allow one-step enrichment of fuel-grade H 2 from shifted syngas for decarbonized H 2 production.

Science & Technology - Other Topics↗
DOE OSTI2026

Temperature Inversions below 1 km from a V-Band Scanning Radiometer at the North Slope of Alaska

A single-channel (56.7 GHz) scanning radiometer was deployed in August 2022 at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska site near Utqiaġvik. The radiometer is designed to provide temperature profiles between 0 and 1 km every 5 min. Averaging kernels show that this single-channel radiometer, taking observations at 10 discrete elevation angles, yields approximately the same information as a seven-channel V-band radiometer scanning three elevation angles. The instrument is able to reproduce the occurrence of temperature inversions between the surface and 1 km and their strength showing a correlation of 0.85, bias of −0.6 K, and slope of 1.04 with respect to radiosondes. Uncertainty in the inversion base height varies from 50 m near the surface to ∼300 m above 0.4 km when compared with radiosondes. Conversely, the inversion top height is overestimated and has higher uncertainty due to the degrading effects of the averaging kernels on the vertical resolution of the retrievals. Thanks to the high temporal resolution of the retrievals, the diurnal cycle of boundary layer temperature was evaluated showing that the radiometer can capture some aspects of the boundary layer thermal structure. The present analysis provides an overview of the capabilities of this simple observing configuration for selected applications.

Atmospheric profilers↗
DOE OSTI2024

Computational Modeling of CO2 Capture By Novel PIM-RU in a Fluidized Bed Riser

The interest in carbon capture, storage, and utilization (CCUS) has increased significantly in the past few decades as it can help mitigate the threat of global warming caused by substantial increase in CO2 emissions due to anthropogenic activities. Although several CO2 capture technologies have been developed, porous solid sorbents, which adsorb CO2 by physisorption, are considered promising candidates for post-combustion CO2 capture because of the easier recovery of adsorbed CO2 and high material stability. Some prominent types of porous solid sorbents are metal-organic frameworks (MOFs), Zeolite, mesoporous silica, and polymer-based sorbents (e.g., polymers with intrinsic microporosity or PIM). Oak Ridge National Laboratory (ORNL) recently developed a novel PIM-based sorbent, referred to here as PIM-RU. The main objective of this work is to investigate the CO2 capture performance of this sorbent using computational fluid dynamics (CFD). While process configuration and reactor design are open questions, a fluidized bed riser was selected as the contactor type for this study.

Aziz, Hossain↗
DOE OSTI2026

Water as a gas separation membrane

Efficient gas separation membranes are essential for carbon capture, biogas upgrading, and hydrogen purification. Inspired by how plants absorb CO 2 through water, we present a membrane platform that uses liquid water as the selective layer. Hydrophilic sub-100-nm pores stabilize water through strong capillary forces, enabling operation at feed pressures above 72 bar under dry and humid conditions. Selectivity is governed by gas solubility in water, while permeance is tuned by adjusting the water layer thickness. Reducing this thickness below 200 nm yields CO 2 permeances up to 11,600 gas permeation units with CO 2 :N 2 , CO 2 :CH 4 , and CO 2 :H 2 selectivities of 40, 26, and 31, respectively, surpassing the performance of state-of-the-art membranes. Operation is sustained for over a week without water loss, and performance scales using commercially available porous polymer supports under mixed-gas crossflow conditions. Water’s dissolution-based transport avoids saturation and reaction-rate limits, enabling a robust, high-performance, and environmentally benign gas separation platform.

08 HYDROGEN↗
DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Spin-selective photocatalysis and quantum transport using ab initio density-matrix dynamics

The overarching goal of this research program is to quantitatively predict out-of-equilibrium quantum dynamics and transport with electrons and spin degrees of freedom coupled to phonons, photons, defects and liquid environments, specifically targeting spin-selective chemistry. Spin polarized carriers, which can be generated at room temperature by circularly-polarized light, provide unique opportunities for creating new reaction pathways and increasing selectivity towards specific pathways. If realized, this can substantially increase the level of reaction control possible in the field of heterogeneous catalysis. Spin, a quantum mechanical entity without a classical counterpart, requires quantum dynamics. Capturing both coherent and incoherent dynamics and accurate correlation of spins, electrons and phonon environments are essential to quantitative description of generation, relaxation and transport, as well as chemical reaction of spin-polarized carriers in molecules and materials promising for spin-photocatalysis.

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

Computational Analysis of Hydraulic Efficiency of Michigan DOT Covers J and K

Drainage structures are used in urban street and highway systems to capture stormwater runoff. These structures typically consist of catch basins fitted with grates, inlets, or combination grate/inlet configurations that collect runoff and convey it through buried drainage systems. They are strategically placed within curb-and-gutter systems to enhance public safety by efficiently removing water from roadways and thereby reducing the risk of hydroplaning. The performance of drainage structures is commonly evaluated in terms of hydraulic efficiency, defined as the percentage of flow captured by the basin relative to the total flow reaching the structure. Understanding the hydraulic performance of these structures allows designers to properly space inlets, resulting in cost-effective designs that also help ensure the safety of the traveling public. MDOT uses a variety of drainage structures for runoff capture, as documented in Michigan Department of Transportation (MDOT) Drainage Manual. Many of these structures incorporate sinusoidal-type grates that are not addressed in HEC-22. Because physical modeling of these structures has been limited, further analysis is needed to verify their capture efficiency. Under current MDOT practice, the capture efficiency of these grates is estimated by assuming performance similar to that of a comparably sized reticuline grate described in HEC22. The first phase of this effort, titled Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C, focused on evaluating the hydraulic performance of MDOT’s Cover C grate. Cover C was selected as the initial test candidate because its sinusoidal pattern is representative of other MDOT grates, while it is typically used in high-volume, higher-speed applications. A similar version, Cover CX, is used on interstate highways but does not include transverse bars for bicycle safety. The current second phase of the study expands this work to evaluate MDOT’s Covers J and K. These grates were selected for additional analysis to further assess the hydraulic performance of MDOT drainage structures that are not directly represented by grate configurations in HEC-22. The results of this phase will build on the findings from the Cover C analysis and support improved understanding of the capture efficiency of MDOT’s standard drainage grates. This report is intended to serve as a companion document to the earlier study, Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C [3]. The present work applies the same overall CFD-based evaluation approach to MDOT Covers J and K and compares the resulting performance trends with those previously identified for Cover C. In particular, both studies assess on-grade interception efficiency, sag-location hydraulic capacity, and the effects of partial obstruction relative to HEC-22-based design estimates.

42 ENGINEERING↗