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At least 595 records · Page 33

Development of an Advanced Multiphysics Simulation Capability for Radiant's Microreactor Design

Argonne National Laboratory and Idaho National Laboratory, through a Department of Energy Gateway for Accelerated Innovation in Nuclear Voucher, supported key analysis needs of Radiant related to (i) air jacket thermal fluid performance, (ii) evaluation of decay heat source terms defining air jacket technical requirements, and (iii) assessment of modeling methodologies employed for core analysis. All of these activities center on numerical simulation of various aspects of Kaleidos using the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, the Cardinal multiphysics application, the OpenMC Monte Carlo code, and the Nek5000 computational fluid dynamics (CFD) code. This project builds upon an earlier Nuclear Energy Advanced Modeling and Simulation (NEAMS) Thermal-Hydraulic (T/H) Center of Excellence (CoE) project focused on initial demonstration of Cardinal multiphysics simulation of High Temperature Gas Reactors (HTGRs) and now focuses on Radiant’s Kaleidos concept.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Preliminary Modeling of Triply Periodic Minimal Surface (TPMS) Structures with RELAP5-3D

This poster goes over preliminary work performed on modeling triply periodic minimal surfaces (TPMS) with RELAP5-3D. The poster starts off with the need for advanced nuclear fuel designs for future reactors, and how TPMS are being researched for this purpose. There is then a focus on what a TPMS is and then moves onto the motivation for why this geometry is being modeled and looked into. The methodology is then shown for how data from different experiments will be used for pre-test predictions and eventual creation of empirical coefficients and multipliers to be used in models. Then there is a show of how data would be compared between the experimental tests, CFD, and RELAP5-3D values. The results from the simulations and comparisons are then presented to show how the CFD and RELAP5-3D compare to each other currently, with no experimental data to compare to for one test model. Results from the second test model are also presented to show that there is stability in the solving of that model.

42 - ENGINEERING↗

Modeling Single and Two-Phase Transport in Thin Porous Layers Using a Composite Continuum-Pore Network Formulation

In this work, a composite continuum-pore network formulation is presented to model single and two-phase transport thin porous layers, such as gas diffusion layers in polymer electrolyte fuel cells (PEFCs) and active electrodes in redox flow batteries (RFBs). The formulation can be integrated into CFD codes, thus combining the ease of implementation of continuum-based modeling and the computational power of pore-network modeling. The composite model includes a control volume (CV) mesh at the layer scale, which embeds a cubic pore network [1,2]. The pore-network model is used to determine analytically local anisotropic effective transport properties (local effective diffusivity and permeability), which are mapped onto the CV mesh to simulate transport in the porous transport layer [3,4]. Good agreement is found between the predicted global effective transport properties (global effective diffusivity and permeability) under dry and wet conditions and previous experimental data reported in the literature for Toray TGP-H series carbon paper. Water saturation distributions are also compared with results obtained using X-ray computed tomography [4]. [1] P.A. García-Salaberri, I.V. Zenyuk, J.T. Gostick, A.Z. Weber, Modeling Gas Diffusion Layer in Polymer Electrolyte Fuel Cells Using a Continuum-Based Pore-Network Formulation, ECS Trans. 97 (2020) 615. [2] P.A. García-Salaberri, Modeling diffusion and convection in thin porous transport layers using a composite continuum-network model: Application to gas diffusion layers in polymer electrolyte fuel cells, Int J. Heat Mass Transf. (2020), submitted. [3] P.A. García-Salaberri, J.T. Gostick, G. Hwang, A.Z. Weber, M. Vera, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of local saturation and application to macroscopic continuum models, J. Power Sources 296 (2015) 440–453. [4] P.A. García-Salaberri, G. Hwang, M. Vera, A.Z. Weber, J.T. Gostick, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of through-plane saturation distribution, Int. J. Heat Mass Transf. 86 (2015) 319–333.

Garcia-Salaberri, Pablo↗

Analytical Study and Experimental Verification of Shear-Thinning Ink Flow in Direct Ink Writing Process

Abstract Direct ink writing (DIW) process is a facile additive manufacturing technology to fabricate three-dimensional (3D) objects with various materials. Its versatility has attracted considerable interest in academia and industry in recent years. As such, upsurging endeavors are invested in advancing the ink flow behaviors in order to optimize the process resolution and the printing quality. However, so far, the physical phenomena during the DIW process are not revealed in detail, leaving a research gap between the physical experiments and its underlying theories. Here, we present a comprehensive analytical study of non-Newtonian ink flow behavior during the DIW process. Different syringe-nozzle geometries are modeled for the comparative case studies. By using the computational fluid dynamics (CFD) simulation method, we reveal the shear-thinning property during the ink extrusion process. Besides, we study the viscosity, shear stress, and velocity fields, and analyze the advantages and drawbacks of each syringe-nozzle model. On the basis of these investigations and analyses, we propose an improved syringe-nozzle geometry for stable extrusion and high printing quality. A set of DIW printing experiments and rheological characterizations are carried out to verify the simulation studies. The results developed in this work offer an in-depth understanding of the ink flow behavior in the DIW process, providing valuable guidelines for optimizing the physical DIW configuration toward high-resolution printing and, consequently, improving the performance of DIW-printed objects.

Engineering↗

Supercritical Reforming of Wet Ethanol for High Efficiency Direct-injection Heavy-duty Compression-ignition Engines

The purpose of the research was to investigate the potential of using a mature bio-fuel in heavy-duty compression ignition engines. By co-optimizing both the fuel characteristics and engine system the potential for a superior outcome was demonstrated. The use of wet bio-ethanol eliminates the majority of the energy intensive distilling and dehydrating fuel production processes, which moves the fuel towards carbon neutral and also lowers the fuel costs. The relatively high water content of the resulting fuel is leveraged in the proposed novel combustion system by incorporating an integrated high efficiency exhaust waste heat recovery system. This results in significantly higher thermal efficiency. In addition the combustion system features low criteria pollutant emissions and the potential to reduce the initial cost of the engine system hardware. Substantial societal benefits are demonstrated through the co-optimization of the fuel and engine system. A computational proof-of-concept study has been performed to demonstrate the potential benefits of a novel wet ethanol heavy-duty compression ignition combustion system featuring integrated exhaust waste heat recovery. A combined in-cylinder closed cycle 3D computational fluid dynamics (CFD) - 1D engine system simulation approach was used. The models were validated to baseline engine data using diesel fuel and then applied to the wet ethanol study. The original concept was to maximize exhaust waste heat recovery through supercritical reforming of the wet ethanol fuel. Phase I simulation results indicated that the optimal solution for maximum engine efficiency gains were realized through maximizing thermo-mechanical recuperation with negligible fuel reformation. The results show the potential to achieve impressive gains in brake thermal efficiency (BTE) over the base diesel engine. The potential to increase BTE up to 20.9% over the base diesel engine was demonstrated, with even larger gains possible through reduced in-cylinder heat transfer losses. The majority of the efficiency gains were realized through integrated high efficiency exhaust waste heat recovery. The concept also has the potential to achieve future ultra-low NO x emissions standards and negligible engine-out soot emissions. The mixing controlled combustion of high temperature wet ethanol features relatively low engine-out NO x emissions without the need for exhaust gas recirculation (EGR). The soot free combustion enabled by the relatively high oxygen content of ethanol also allows for the use of stoichiometric mixing controlled combustion, which is not practical with diesel fuel. When stoichiometric combustion is used a simple passive 3-way catalyst can be used for exhaust emissions after-treatment and near zero tailpipe emissions. The Phase I simulations results have defined the system layout and requirements in preparation for the Phase II experimental proof-of-concept study. The potential applications of the research include most current applications of diesel engines. The Phase I study focused on heavy-duty on-highway class 8 trucks. However, virtually any application that requires highly efficient clean power generation would benefit from the novel engine system proposed. The results indicate substantial fuel cost savings and reduced greenhouse gas emissions with similar or reduced initial system hardware costs compared to modern diesel engine systems.

09 BIOMASS FUELS↗

Computational Fluid Dynamics Simulations to Predict Oxidation in Heat Recovery Steam Generator Tubes

Heat Recovery Steam Generators (HRSGs) are widely used across United States in combined cycle power plants to recover waste heat from the gas turbine (GT). HRSGs are used either to generate electricity or to produce process steam for industrial applications. The primary components of HRSG consists of a duct and a heat exchanger (HX). It is known across the power industry that the high temperature oxidation and ensuing exfoliation problem is a major cause for the damage of HX materials of HRSG. Alloys and/or coatings that can prevent or mitigate oxidation are very expensive, therefore they must be used or applied on the select regions of the HX tubes where the tendency of oxide formation is the highest. The main goal of this project is to identify such regions through Computational Fluid Dynamics (CFD) simulations. Therefore, in this work, we developed a CFD framework using commercial code StarCCM+ for the prediction of the fluid flow and heat transfer in a HRSG and associated oxidation inside the tubes of the HX. The developed CFD framework was verified and validated with experimental data before deployment. We also developed an innovative method to model the effect of the fins on the heat transfer and the pressure drop using a porous media model (PMM) approach to keep the mesh size within reasonable limits. After validation, we performed high-fidelity CFD simulations of a real-scale HRSG using the PMM, with High Performance Computing (HPC) resources of ORNL. From the simulation results, we acquired oxide thickness maps for all the tubes of the select HX sections of HRSG prone to oxidation. These oxide maps can inform regions of the HX tubes that requires oxide-resistant coatings, thereby guiding engineers for cost-efficient manufacturing of the HX that can combat oxidation in HRSGs.

36 MATERIALS SCIENCE↗

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

This report documents the benchmarks being developed and simulations performed using tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, utilizing MSRE experimental data. In FY23, three main work scopes were investigated under the NEAMS MSR work package at ANL. The first scope investigated the Griffin-SAM coupling model for simulating the pump startup transient experiment of MSRE. The analyses start with a simple model (single-channel, single-lattice), gradually adding more details (multi-channel, full-core) into the model. The results show that the reactivity loss curve is very sensitive to the axial boundary conditions and the radial core discretization. The simple model can predict a similar reactivity trend as that of the more sophisticated model, which is likely due to error cancellation. Accurately modeling the axial boundary condition may further improve the reactivity trend but would require significant efforts to generate the mesh of the MSRE inlet and upper plenum. The core channel radial discretization for the Griffin-SAM coupled model also depends on the flow distribution. Given the complex geometry in the inlet plenum, the flow distribution needed to be calculated from CFD analysis, which was performed using the NekRS code. This analysis employed a MSRE CAD model developed by Copenhagen Atomics. The CAD model was disassembled to keep the inlet plenum region only, which was subsequently cleaned and modified so that the mesh generated is under the memory limit. The results are merged to a few radial regions to show that the flow rate is highest in the central region. This would be useful for future improvement of the Griffin-SAM coupling model of the MSRE core. The last task investigated is tritium transport modeling using the standalone SAM code. This task aimed to initiate the effort to demonstrate and validate the tritium transport model implemented in SAM. The preliminary investigation employed an MSRE model consisting of the primary loop. Three tritium transport pathways were examined including the retention in the graphite, the permeation through the HX tube wall, and the removal from the off-gas system. The results compare well with the MSRE data, but improvements are still needed on the initial conditions (i.e., the present state may not have reached equilibrium), the boundary conditions, the off-gas system modeling, and a better numerical strategy to reach the equilibrium state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Physics-Driven Convolutional Autoencoder Approach for CFD Data Compressions: Preprint

With the growing size and complexity of turbulent flow models, data compression approaches are of the utmost importance to analyze, visualize, or restart the simulations. Recently, in-situ autoencoder-based compression approaches have been proposed and shown to be effective at producing reduced representations of turbulent flow data. However, these approaches focus solely on training the model using point-wise sample reconstruction losses that do not take advantage of the physical properties of turbulent flows. In this paper, we show that training autoencoders with additional physics-informed regularizations, e.g., enforcing incompressibility and preserving enstrophy, improves the compression model in three ways: (i) the compressed data better conform to known physics for homogeneous isotropic turbulence without negatively impacting point-wise reconstruction quality, (ii) inspection of the gradients of the trained model uncovers changes to the learned compression mapping that can facilitate the use of explainability techniques, and (iii) as a performance byproduct, training losses are shown to converge up to 12x faster than the baseline model.

auto-encoders↗

Deterministic Calibration of MFiX-PIC, Part 1: Settling Bed

The Particle-in-cell (PIC) numerical approach for modeling granular solids in fluid flow has gained significant interest in recent years. Valued for its often shorter time-to-solution, the PIC formulation relies on modeling statistical groupings of particles called parcels in cooperation with a solids stress model to affect local solids velocity. This is in contrast to the discrete element model (DEM) where every particle in a system is modelled individually and directly coupled to local solids velocity through Newtonian mechanics. The U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) develops and maintains Multiphase Flow with Interphase eXchanges (MFiX), a collection of open-source computational fluid dynamics (CFD) solvers. Included in the MFiX suite are traditional two-fluid model (TFM) and DEM solvers, and a recently added PIC solver (NETL, 2021). In general, PIC methodologies offer an accuracy trade-off in lieu of computational speed; and therefore, it is important to assess the credibility of MFiX-PIC simulations. For this purpose, a systematic verification, validation and uncertainty quantification (VVUQ) effort was initiated at NETL to assess the new PIC solver

42 ENGINEERING↗

Validation of Computational Fluid Dynamics Simulations for Biological Performance Assessment in Hydropower units (Final Report)

The biological performance assessment (BioPA) toolset developed by Pacific Northwest National Laboratory (PNNL) estimates the relative biological performance of fish passage at a hydroelectric power turbine unit. The tool is based on the use of computational fluid dynamics (CFD) and fish biological response relationships. The recent release, BioPA-v3, is based on directly computed trajectory and collision of material Lagrangian particles using CFD simulation codes rather than the prior version that relies on Tecplot to compute streamtrace trajectories. Before modifying the toolset, a series of validation tests were performed at the various steps of modification in the toolset. Validation is a critical step of any numerical investigation that reflects the accuracy and reliability of the predicted results. It raises the confidence level of the user to use the modified version of the BioPA toolset. Several test cases were simulated and compared, where available, to observed data. The trajectory and collision of the small spherical and cylindrical particles in a water flume were compared to in-house experiments. The CFD predicted collision rate and flow field compared well with experimental observation for vane array and large cylinder as target bodies. Next, the CFD-predicted flow field and hydraulic performance of a laboratory-scale model of a Francis turbine was also successfully validated. Note that the trajectory of the particles is significantly affected by the flow field in such extreme conditions. In addition to the particle trajectories and flow field, the collision detection method employed in the CFD simulations was also successfully validated. The CFD predicted impact velocity, collision time, velocity, and trajectory of a sphere excellently matched with analytical value for a bouncing ball in the elastic collision. A similar approach was also tested and successfully validated for a collision of sphere with a 45° inclined plane. After successfully validating different cases, the BioPA toolset was modified to use direct output of the CFD prediction and the new version can be used in evaluating biological performance at hydroelectric turbines.

13 HYDRO ENERGY↗

Impact of high-fidelity temperature feedback modeling on fusion blanket neutronics

Accurate modeling and simulation of neutron and gamma transport and interactions within fusion tokamaks represents a critical area of research for fusion energy development. This paper presents a method to couple computational fluid dynamics (CFD) results to high-fidelity neutronics analyses, to explore the fusion neutronics’ feedback to blanket temperature and density. This method is demonstrated on a sector model of a tokamak with immersion molten salt blanket, and the relative differences in tritium breeding ratio (TBR) with spatially-resolved temperature modeling are explored. Additionally, the influence of higher fidelity neutronics results on the subsequent CFD analysis is explored. Results show that global TBR changes $<$0.1% due to temperature spatial distribution modeling. However, local TBR in areas with high temperature variability can have up to ∼4% difference.

blanket fusion↗

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗

Performance evaluation of a wrapped around condenser for heat pump water heater applications

In this report, accurate performance evaluation of a wrapped-around condenser for heat pump water heaters (WHPWH) is critical since the COP of the system depends heavily on thermal stratification and condenser design. An analytical, quasi-steady state heat balance method has been developed to determine the optimal spacing between adjacent channels, tube diameter, tube shape, and total refrigerant charge amount for the condenser. The heat transfer rate is compared among three approaches: the refrigerant thermodynamic model, the condenser-wrap fin model, and the analytical natural convection model on the inside of the tank for the three regions based on the refrigerant phase (e.g., super-heated, saturated, or subcooled). The heat transfer rate was predicted by a combination of slug-plug and annular flow for a D-shaped helical tube. Experimental data were used as boundary conditions for validating the model. The rate of heat transfer based on tube shape and tank wall temperatures was compared by CFD analysis. Parametric analysis indicates a tradeoff between refrigerant mass, pressure drop, tube diameter, and tube length to maximize the heat transfer rate. The model suggests the saturated region length can be extended by 400%, and the condenser pressure drop can be reduced by 23% with an optimal spacing pattern.

42 ENGINEERING↗

Tool-workpiece stick-slip conditions and their effects on torque and heat generation rate in the friction stir welding

Friction stir welding (FSW) has found increased applications in automotive and aerospace industries due to its advantages of solid-state bonding, no fusion and melting, and versatility in various working conditions and material combinations. However, the relationship among processing parameters, material properties, and bonding extent and fidelity remains largely empirical, primarily because of the lack of the mechanistic understanding of the tool-workpiece frictional behavior that affects our subsequent understanding of microstructural evolution and interface bonding formation. While the tool-workpiece stick-slip condition is believed to dictate the resulting torque and heat generation rate during the welding process, it remains rare and elusive to conduct a quantitative experimental measurement of such interfacial field. On the other hand, numerical simulations based on Computational Fluid Dynamics (CFD) rely on ad hoc assumptions of interfacial pressure and shear-stress conditions, but predictions can only be validated via the medium- and far-range temperature field which is known to be insensitive to the interfacial frictional behavior. This work first presents a comparison among two CFD-based simulation methodologies and the Coupled Eulerian Lagrangian (CEL) model in finite element method, the last of which uses the Coulomb friction so that the stick-slip is naturally developed. Based on the Hill-Bower similarity relationship in the contact analysis, an analytical model is developed here to prove why a constant stick-slip fraction will be developed in the steady state, to correlate the stick-slip fraction to processing parameters such as the tool spin rate, and further to derive dimensionless functions for torque and heat-generation-rate predictions. Pros and cons of various numerical approaches in predicting stick-slip are discussed, and our analytical model has been found to agree well with our numerical simulation and literature experimental results. These analyses provide the critical strain-rate and temperature fields that are needed for the bonding analysis in our future work.

36 MATERIALS SCIENCE↗

State-of-the-art and review of condensation heat transfer for small modular reactor passive safety: Experimental studies

Here this study focused on state-of-the-art and review of condensation heat transfer for small modular reactors (SMR). Nuclear reactors adopt passive containment cooling systems (PCCS) for accident mitigation, containment integrity, and primarily to maintain the last barrier for radioactive particle release to the environment during and beyond design-basis accidents. However, improving the effectiveness of the PCCS is more critical for the SMR than for commercial reactors to ensure higher safety margins and compactness. In the PCCS of SMR, due to its smaller size containment, the filmwise condensation (FWC) is dominant. Therefore, this study emphasized the FWC. Earlier condensation studies for the PCCS did not make SMR the primary focus, so a critical review for formulating the state-of-the-art was necessary. Part-1 of this study covered the review of physics phenomena, previous experimental studies with a brief overview of associated test facilities and empirical correlations. This study identified a research gap with the condensation test data scaling relations by using the information and findings of the previous PCCS studies and applied them to the SMR system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Background-Oriented Schlieren Velocimetry of Helium Coolant Flow in Additively Manufactured Channels

High-pressure helium gas cooling is an attractive solution for thermal management of the fusion blanket first wall, as this coolant is chemically and neutronically inert and separable from hydrogenic species. However, due to the low thermal mass of helium, geometric optimization of these channels is required to provide sufficient cooling at manageable flow rates and pumping burdens. Increasingly, analysis and optimization of these coolant channels rely on computational fluid dynamics (CFD) simulations, and these require relevant experimental data for turbulence model validation. Toward this end, a high-pressure helium gas flow visualization system has been employed to image the flow of helium in flow channels with one-sided heating, mimicking the blanket first wall environment. Flow of helium at 4 MPa pressure and flow rates up to 68 g/s (Reynolds number 57 000) is supplied to rectangular channel test sections, with uniform heating applied to the bottom wall of the channel at heat fluxes varied between roughly 50 and 130 kW/m2. A high-speed camera is used to image index of refraction (IOR) gradients in the fluid via background-oriented schlieren (BOS), and temperature and pressure instrumentation are used to characterize thermal-hydraulic performance of each channel. Cross correlation of time-resolved BOS images is then used to calculate time-averaged 2-D helium velocity fields. Flow in additively manufactured (AM) channels is examined in this manner, including both featureless channels and those containing baffling as a heat transfer enhancement. The flow distribution seen in the featureless case differs significantly from that seen in prior simulations, whereas the flow in the baffled case shows the predicted behavior of flow forced along the heated wall. This augmented flow distribution is seen to increase the heat transfer coefficient in the baffled test section. Here, strategies are discussed for ongoing and future validation of these simulations, with the aim of model deployment for blanket cooling design and optimization.

Additive manufacturing↗

Performance and Emissions of an SI Engine Fueled With DME-Propane Blends

Dimethyl Ether (DME) is an alternative fuel that can be produced renewably and has the potential for lower CO and NOx emissions than conventional petroleum-based fuels. Blending DME with another gaseous fuel such as propane, which has a lower knock tendency than gasoline, can allow this fuel to be leveraged on SI engines. In this study, the use of DME-propane blends on a spark ignition (SI) engine was studied via computer simulations in order to understand the impact on engine performance and emissions and to identify the knock limitations of using such fuel blends. A 2L Hyundai SI engine was modeled in GT Power and the model was validated by comparing it with computational fluid dynamics (CFD) simulation results. Starting from pure propane, DME was added incrementally until knock was observed in the engine. Results indicate that it is feasible to run propane with DME percentages up to 35% before severe knock impacts were observed. The BTE was higher, but the BSFC also increased for DME-propane blends as compared to gasoline. Here, an increase in NOx emissions was detected along with a significant decrease in CO emissions. CO 2 emissions declined for propane as compared to gasoline but increased with the addition of DME.

alternative fuels↗