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At least 325 records · Page 18

One-step transformation of biomass to fuel precursors using a bi-functional combination of Pd/C and water tolerant Lewis acid

Direct one-pot transformation of lignocellulosic biomass has been developed as an effective and sustainable strategy to produce fuel blend stocks and high value chemical building blocks. In this wok, a bi-functional catalyst system consisting of palladium supported on carbon (Pd/C) and metal triflates (i.e., Sm(OTf) 3 , La(OTf) 3 , and Cu(OTf) 2 ) were shown to promote the biomass liquefaction in both hot-compressed water and supercritical ethanol medium, converting fir wood into oxygenated compounds. We report the highest bio-oil yield from hydrothermal liquefaction (HTL) was 10.47 wt% over Pd/C whereas the highest bio-oil yield of 49.71 wt% was achieved from supercritical ethanol liquefaction (SCEL) over the bi-functional catalyst system of Pd/C and La(OTf) 3 . Higher heating values, carbon recovered values and boiling point distributions were further determined for elucidating the physical properties of the bio-oils. Gas chromatography mass spectrometry (GC–MS) analysis of the bio-oils revealed the chemical composition of the bio-oils. Substituted phenols and cyclopentenone/cyclopentanone type compounds consisted of more than 60 area% of the total products from HTL, whereas phenol and esters represented the major products from SCEL. The major reaction pathways are proposed based on the GC–MS results, which include depolymerizaton, isomerization, dehydration, condensation, and hydrogenation.

09 BIOMASS FUELS↗

An Experimental Study of Uncertainty Considerations Associated with Predicting Auto-ignition Timing using Livengood-Wu Integral Method

The application of the Livengood-Wu (LW) integral method as a tool to estimate knock onset in spark ignited (SI) engines and combustion phasing in advanced compression ignition (ACI) engines has been demonstrated through simulations several times. In this study, the effect of uncertainties associated with parameters required for the LW integral method, when used as a tool for model based control of ignition timing in an ACI engine, were experimentally studied using five full boiling range gasoline fuels. As a first step, the method was applied to experimental data from a rapid compression machine and it was found that the ability of the LW integral method to predict ignition timing was very sensitive to the performance of the chemical kinetic model of each fuel. The method was subsequently applied to experimental data from a single-cylinder gasoline engine with simple approximations for the LW integral input parameters, and it was found that the predicted time of ignition was significantly different from the actual start of combustion. Systematic evaluation of various parametric uncertainties conducted thereafter showed that the uncertainty in cylinder charge temperature has the greatest influence. Improved methods of estimating cylinder charge temperature are proposed to account for the previously determined corrections, to enable the use of the LW integral method for model based control of ignition timing.

Compression Ignition↗

Gasoline fuels properties for multi-mode operation – Observations in a GDI and the CFR engine

The combustion behavior of five full boiling range RON98 gasoline blends was evaluated for multi-mode operation in a GDI and the CFR octane rating engine. The GDI engine tests were conducted with stoichiometric air-fuel ratio in spark-ignition (SI), and with air-diluted homogeneous charge compression ignition (HCCI) mode. In the CFR engine, the knocking combustion was analyzed under standard RON testing conditions at both peak knocking lambda and stoichiometric air-fuel ratios, whereas compression ignited operation was characterized by utilizing the HCCI number test protocol. Disparate knock limited SI and HCCI combustion behavior was observed for the test fuels, despite four of the fuels having the same RON and octane sensitivity. It was found that knock-limited combustion phasing in the GDI engine did not align well with the RON. However, a detailed comparison of knock-limited SI operation in the GDI and CFR engine revealed that a more appropriate effective RON based on a common knock intensity metric (MAPO) and stoichiometric air-fuel ratio resulted in comparable knock characterization between the two engine platforms. Furthermore, the critical intake air temperature and the critical compression ratio were proposed to characterize knock-limited SI operation, while the minimum intake air heating and compression ratio were used to define a fuel's autoignition propensity for compression ignition operation in the GDI and CFR engine, respectively. Finally, each fuel's characteristic compression ratio needed to obtain knock-limited SI (KLSI) and HCCI operation was used to calculate an effective multi-mode octane number (MM-ON) based on the primary reference fuel blends.

33 ADVANCED PROPULSION SYSTEMS↗

A systematic method for selecting molecular descriptors as features when training models for predicting physiochemical properties

Machine learning has proven to be a powerful tool for accelerating biofuel development. Although numerous models are available to predict a range of properties using chemical descriptors, there is a trade-off between interpretability and performance. Neural networks provide predictive models with high accuracy at the expense of some interpretability, while simpler models such as linear regression often lack in accuracy. In addition to model architecture, feature selection is also critical for developing interpretable and accurate predictive models. We present a method for systematically selecting molecular descriptor features and developing interpretable machine learning models without sacrificing accuracy. Our method simplifies the process of selecting features by reducing feature multicollinearity and enables discoveries of new relationships between global properties and molecular descriptors. To demonstrate our approach, we developed models for predicting melting point, boiling point, flash point, yield sooting index, and net heat of combustion with the help of the Tree-based Pipeline Optimization Tool (TPOT). For training, we used publicly available experimental data for up to 8351 molecules. Our models accurately predict various molecular properties for organic molecules (mean absolute percent error (MAPE) ranges from 3.3% to 10.5%) and provide a set of features that are well-correlated to the property. This method enables researchers to explore sets of features that significantly contribute to the prediction of the property, offering new scientific insights. To help accelerate early stage biofuel research and development, we also integrated the data and models into a open-source, interactive web tool.

09 BIOMASS FUELS↗

Blended fuel property analysis of butyl-exchanged polyoxymethylene ethers as renewable diesel blendstocks

Methyl-terminated polyoxymethylene ethers (MM-POMEs), having the formula CH 3 O-(CH 2 O)n-CH 3 (n = 3-6), are a class of oxygenates with desirable diesel-like fuel properties including high cetane number and low soot formation. However, their low energy density and high water-solubility present barriers to their adoption. Both concerns were recently addressed by our research group by synthesizing a mixture of POME structures having butyl end-groups and n = 1-6, termed B*POME1-6. B*POME1-6 maintained the advantageous properties of the parent MM-POMEs, and exhibited improved energy density and most notably, dramatically decreased water solubility. For evaluation against a set of criteria for a blended diesel blendstock, a 20 vol% blend of B*POME1-6 with a base diesel fuel was investigated here. Oxidation stability, cetane number, sooting tendency, lubricity and conductivity were improved in the B*POME1-6 blend compared with the base diesel, while also maintaining the flash point, cloud point, energy density, viscosity, and boiling point requirements. The B*POME1-6 product demonstrated a synergistic blending behavior at 10 vol% and a linear blending behavior at 20-30 vol% blends, in agreement with similar POME blends at comparable blend levels. Finally, common environmental and toxicity models performed on B*POME1-6 component molecules suggested they have a greater propensity to partition into the water compartment compared to a common diesel surrogate, but with a lower tendency to bioaccumulate.

33 ADVANCED PROPULSION SYSTEMS↗

Combustion dynamics of crude and upgraded Thermal DeOxygenation oils in a compression ignition engine

Thermal DeOxygenation (TDO) is a robust thermochemical conversion scheme to produce hydrocarbons from biomass feedstock. The process targets the carbohydrate fraction of biomass to yield a broad mixture of primarily aromatic hydrocarbons within a boiling point range of 348–798 K with low oxygen content (<4 wt%). The resulting materials are amenable to traditional hydrotreating and distillation processes with approximately 70% by mass in the distillate fuel range. The simple conversion scheme combined with commercially viable upgrading routes makes TDO oils a feasible alternative fuel for transportation applications. Here this paper is the first systematic treatment of fit-for-purpose testing of TDO oils in a compression ignition engine. Blends of partially upgraded TDO oils (e.g. whole oil, distilled oil, hydrotreated oil and hydrotreated-distilled oil) are prepared with certified ultra-low sulfur diesel at 5%, 10%, 15% and 20% by volume. The resulting fuels are analyzed for fuel characteristics and combustion dynamics in an instrumented single-cylinder compression ignition engine. All fuel blends at 10% blend level by volume exhibited adequate engine performance. Hydrotreating of the oils is a necessary step to meet cetane number and EPA soot emissions requirements at 20% blend volume. Combined distillation and hydrotreatment meet or exceed all fuel specification and engine performance benchmarks. Partially upgraded TDO oils are suitable fuel options for compression ignition applications.

42 ENGINEERING↗

A structured framework for predicting sustainable aviation fuel properties using liquid-phase FTIR and machine learning

Sustainable aviation fuels have the potential to improve efficiency, reduce emissions, and enhance energy security. To help identify viable sustainable aviation fuels and accelerate research, machine learning models have been developed to predict relevant physicochemical properties. However, many models have limited applicability, leverage data from complex analytical techniques with confined spectral ranges, or use feature decomposition methods that offer limited interpretability. Using liquid-phase Fourier Transform Infrared (FTIR) spectra, this study presents a structured method for creating accurate and interpretable property prediction models for neat molecules, aviation fuels, and blends. Liquid FTIR spectra can be collected quickly and consistently, offering high reliability, sensitivity, and component specificity using less than 2 ml of sample. The method first decomposes FTIR spectra into fundamental building blocks using non-negative matrix factorization (NMF) to enable scientific analysis of FTIR spectra attributes and fuel properties. The NMF features are then used to create five ensemble models for predicting final boiling point, flash point, freezing point, density at 15°C, and kinematic viscosity at -20°C. All models were trained using experimental property data from neat molecules, aviation fuels, and blends. The models accurately predict key properties across a broad range of neat molecules and representative fuels and blends, while enabling interpretation of relationships between compositional elements, such as functional groups or chemical classes, and their resulting properties. This demonstrates strong potential to support sustainable aviation fuel research and development. The models and data are available on an interactive web tool.

Fourier transform infrared spectroscopy↗

Evaluation of methods and improvement of predictions for specification properties of petroleum-based and alternative aviation fuels

To support our research and process modeling for liquid fuels, including blends, from petroleum and synthetic sources such as from biomass intermediates, we evaluated composition-based prediction methods and improved predictions for five key specification properties of petroleum-based and alternative aviation fuels, namely distillation temperatures (10 % distilled, t 10 , and final boiling point, t FBP ), density, flash point, net heat of combustion, and freezing point. The types of fuels included were petroleum-based jet fuels, jet-fuel surrogate mixtures, synthetic blending components obtained from different sources, and blends of Jet A with many synthetic blending components. Expanded datasets to update associated parameters allowed significant improvements for one of the prediction methods used in earlier work, namely the Modified Weighted Average method published initially by Shi et al. By considering the importance of lighter compounds for flash points and heavier compounds for freezing points, the revised Modified Weighted Average method was further improved. For liquid density, the revised Modified Weighted Average method gave the best overall results. The revised Modified Weighted Average method, the American Society for Testing and Materials D7215 method, and the D7215 method modified by another group gave comparable results for flash point, while the revised Modified Weighted Average and D3338 methods gave the best results for net heat of combustion. Freezing point was well predicted using the revised Modified Weighted Average method and showed the most significant improvements over current predictions. Distillation temperature t 10 was not well predicted, while t FBP was predicted with a mean absolute error comparable to experimental reproducibility.

09 BIOMASS FUELS↗

An Experimental Study of the Solubility of Rare Earth Chloride Salts (La, Nd, Er) in HCl Bearing Water Vapor from 350 – 425 °C

In this work, the solubilities of the rare earth chlorides REECl 3 , where REE = (La, Nd, Er), were measured in HCl bearing water vapor from 350 – 425°C with water partial pressures ranging from 8 – 170 bar. Solubility data were fit to the Pitzer-Pabalan quasi-chemical model in order to extract thermodynamic parameters for the formation of the gaseous REE-chloride-water clusters REECl 3 (H 2 O) n . The data show that the solubility of the REE chlorides are orders of magnitude higher than salts such as NaCl or CuCl at low water fugacities, despite their sublimation energies being substantially higher. This enhanced solubility is likely due to the high enthalpy associated with binding a single water molecule to form the species REECl 3 (H 2 O), with derived enthalpies ranging from –378 to –465 kJ/mol. Addition of further water molecules to form higher order clusters (n > 1) involves enthalpy changes of ~ -20 kJ/mol, and are in effect thermodynamically suppressed over the temperature range 350 – 425°C. Despite the enhanced solubility of small REECl 3 water clusters, simulations of boiling processes demonstrate that the REE show highly conservative behavior, partitioning strongly into the dense aqueous phase. Not surprisingly, the presence of phosphates in the system makes this effect even more pronounced, completely immobilizing the REE. This would reduce transport in both the vapor and aqueous phase to negligible levels. However, we suggest that vapor phase transport of the REE may play a significant role in systems having a relatively low partial pressure of water (below the saturation point), where the relatively high stability of the first hydrated REE chloride clusters (REECl 3 (H 2 O) and REECl 3 (H 2 O) 2 ) will give a preference for gas transport of the REE relative to other elements. This can likely happen in systems involving a gas/melt exchange in fumarolic exhalations, where water vapor discharges at relatively low (close to atmospheric) pressures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Reservoir Temperature Estimator (RTEst): A multicomponent geothermometry tool

The Reservoir Temperature Estimator (RTEst) is a multicomponent geothermometry tool for estimating reservoir geochemical parameters including reservoir temperature, CO 2 fugacity, mass of water lost or gained, and a reaction factor. It estimates these parameters and their associated uncertainties by minimizing an objective function that is the weighted sum of squares of the saturation indices of a user-selected set of minerals believed to be equilibrated with the reservoir fluid. RTEst accomplishes these estimates by combining the geochemical modeling capabilities of The Geochemist’s Workbench® with the optimization/parameter estimation resources of PEST®. An included interface aids the user in selecting plausible mineral phases to comprise the objective function and calculates their weighting factors. The working principles of RTEst are described and its efficacy is illustrated by presenting results of its application to various geothermal fields with known conditions. These examples show RTEst can account for the alteration of ascending reservoir fluid by mineral (calcite) re-equilibration with changes in temperature, reconstruct waters with CO 2 loss, correct for the deficit of water and other volatiles (CO 2,gas , H 2 S gas ) from boiling, and determine the amount of mixing of thermal and non-thermal waters. RTEst can use data with basis species below detection limit, missing, or unreliable either by assuming equilibrium with a controlling mineral (fixed-analyte method) or by treating the analyte concentration as an optimization parameter. The inverse of variance weighting method included in RTEst provides more representative results than either the normalization or unit weighting methods. Finally, the ability of RTEst to calculate reservoir temperatures, gas fugacity, and mixing fractions demonstrates its usefulness as a tool for evaluating geothermal systems.

15 GEOTHERMAL ENERGY↗

A green degumming approach for lignocellulosic kenaf bast using ethanolamine deep eutectic solvent

Traditional chemical degumming methods for lignocellulosic bast fibers pose substantial challenges, especially when dealing with kenaf bast, which has a high lignin content. Here, these challenges include severe pollution and low efficiency, etc. Therefore, this study developed a novel, green, and efficient degumming approach for lignocellulosic kenaf bast, leveraging choline chloride-ethanolamine (ChCl-ETA) alkaline deep eutectic solvent (DES). The efficacy of the ChCl-ETA DES based degumming method was validated through comprehensive chemical composition analysis, scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), thermogravimetric analysis (TG), and two-dimensional (2D) nuclear magnetic resonance (NMR) spectroscopy. Subsequently, the optimal degumming conditions, with a choline chloride to ethanolamine ratio of 1:6 and a degumming temperature of 120 °C, were determined based on the results of the residual gum content. Significantly, the recycled ChCl-ETA DES mixtures could maintain a degumming capacity (revealed by the residual gum content of degummed fibers) comparable to that of the conventional double-boiling method for at least five degumming cycles without purification. Given its low-pollution process and high efficiency, this developed method holds great potential for industrial-scale applications of lignocellulosic bast fibers.

Choline chloride↗

Falling-film thermosyphons: Application to water harvesting from humid gas streams

Water harvesting from humid gas streams is central to fresh-water production, desalination, and particulate removal from combustion gas streams. Two-phase thermosyphons are well suited for these applications due to their very low thermal resistance, but have several operating limits at the high heat flows required for such applications. This work introduces the falling-film thermosyphon for large-scale condensation applications. Working fluid is pumped to the top of the evaporator to provide the evaporating liquid film on the inner tube wall, rather than by vapor condensation. The flooding, dry-out and pool-boiling limits are eliminated, resulting in significantly higher maximum heat fluxes for the same physical evaporator size. Furthermore, the condenser no longer needs to be located vertically above the evaporator, which allows for a standard steam condenser to be used. A model for the condensation process in humid air was developed that estimates the fluid and heat transfer and is confirmed experimentally. Further benefits include the use of a high-thermal-conductivity polymer material for the evaporator section to minimize corrosion, and the ability to impose a temperature boundary condition on the evaporator, which is made possible due to the elimination of a liquid pool.

42 ENGINEERING↗

Heat and mass transfer during a sudden loss of vacuum in a liquid helium cooled tube - Part III: Heat deposition in He II

A sudden loss of vacuum can be catastrophic for superconducting particle accelerators. In such an event, air leaks into the liquid-helium-cooled accelerator beamline tube and condenses on its inner surface, causing rapid boiling of the helium and dangerous pressure build-up. Understanding the coupled heat and mass transfer processes is important for the design of the beamline cryogenic system. Our past experimental study on nitrogen gas propagating in a copper tube cooled by normal liquid helium (He I) has revealed a nearly exponential slowing down of the gas front. A theoretical model that accounts for the interplay of the gas dynamics and the condensation was developed, which successfully reproduced various key observations. However, since many accelerator beamlines are actually cooled by superfluid helium (He II) in which the heat transfer is via a non-classical thermal counterflow mode, we need to extend our work to the He II cooled tube. This paper reports our systematic measurements using He II and the numerical simulations based on a modified model that accounts for the He II heat-transfer characteristics. By tuning the He II peak heat-flux parameter in our model, we have reproduced the observed gas dynamics in all experimental runs. The fine-tuned model is then utilized to reliably evaluate the heat deposition in He II. Finallly, this work not only advances our understanding of condensing gas dynamics but also has practical implications to the design codes for beamline safety.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A unified non-equilibrium phase change model for injection flow modeling

The homogenous relaxation model (HRM) is one of the most widely used models to describe the liquid- gas phase transition. However, in its original formulation, it is unable to handle multispecies vapor-liquid equilibrium (VLE), which limits its applicability to single-component fluids. In this work, a unified non-equilibrium phase change model that considers the VLE of multicomponent mixtures is proposed building upon the HRM's structure. A time factor is introduced to mimic the effect of different phase change timescales due to different mechanisms, e.g., cavitation, flash-boiling, and evaporation. Here to assess the model's performance, computational fluid dynamics simulations of the internal and near-nozzle injection flow of the Engine Combustion Network's Spray G injector were performed using the nine-component PACE-20 fuel with both the unified model and the original HRM. The predicted fuel density in the near-nozzle region matched well with X-ray tomography measurements. The simulation results indicated that, whereas the HRM failed to capture the vaporization due to convective mixing between the fuel and ambient gas, the unified model performed well in predicting the mixing-driven vaporization and the corresponding evaporative cooling. Further comparisons using the nine-component fuel formula and a single-component fuel surrogate demonstrated the unified model's ability to predict preferential vaporization, which affects the predictions of local mixture composition and rate of vaporization. Finally, it is shown that the unified model is capable of representing multiple phase change mechanisms, and the relaxation time factor plays an important role in determining the degree of phase change due to the different mechanisms.

33 ADVANCED PROPULSION SYSTEMS↗

Effective thermal conductivity of insulation materials for cryogenic LH 2 storage tanks: A review

An accurate estimation of the effective thermal conductivity of various insulation materials is essential in the evaluation of heat leak and boil-off rate from liquid hydrogen storage tanks. In this work, we review the existing experimental data and various proposed correlations for predicting the effective conductivity of insulation systems consisting of powders, foams, fibrous materials, and multilayer systems. We also propose a first principles-based correlation that may be used to estimate the dependence of the effective conductivity as a function of temperature, interstitial gas composition, pressure, and structural properties of the material. We validate the proposed correlation using available experimental data for some common insulation materials. Further improvements and testing of the proposed correlation using laboratory scale data obtained using potential LH 2 tank insulation materials are also discussed.

08 HYDROGEN↗

Effect of micro-fin tube geometry parameters on evaporator material savings

A Performance Evaluation Criteria (PEC) analysis is presented that explores the influence of the micro-fin tube geometry on the required material volume. The analysis was done using a local flow boiling model, which can quantify the effect of fin parameters and the tube diameter. The PEC was done while requiring that the compared surfaces satisfy the same heat duty and pressure drop. The following tube parameters and ranges were explored: tube diameter (3 mm ≤ D o ≤ 6 mm), fin base thickness (0.12 mm ≤ t bf ≤ 0.29 mm), helix angle (6° ≤ α ≤ 30°), fin apex angle (11° ≤ β ≤ 22°), total number of fins (43 ≤ n f ≤ 70), and the fin height (0.11 mm ≤ e ≤ 0.3 mm). The tube that provided the smallest material requirements within the examined parameter ranges had: D o = 3 mm, t bf = 0.12 mm, α = 6°, β = 11°, n f = 43, and e = 0.3 mm. In general, small D o and t bf and large n f and e provided the best performance and work to minimize the required material volume to provide a given heat duty and pressure drop. The helix and the fin-tip apex angles were found to have very little influence on the performance for the examined range of parameters and angles associated with the lowest production cost should be chosen.

Evaporation↗

The role of annealing and grain boundary controls on the mechanical properties of limestones and marbles

Chemical and mechanical processes are coupled in many geological and geochemical environments. Reactive processes anneal defects and restructure grain boundaries, modifying their elastic properties, levels of internal friction, wave propagation rates and fracture behaviors. The nature of these changes is, however, contingent on the initial state of the rock. Here, in this study, impulse excitation was used to measure changes in mechanical properties as a function of dry and steam heating time at 300 °C for three carbonate rocks: Carrara marble, Carthage marble (Burlington Limestone), and Texas Cream limestone (Edwards limestone), with initial porosities of about 1 %, 3 %, and 27 %, respectively. Frequency-dependent phenomena along with mineral recrystallization were observed. This was coupled with small-angle X-ray and neutron scattering analysis to determine the relationship between changes in bulk mechanical and microstructural properties. An observed decrease in both the Young's and shear moduli in the experimental limestones as a function of heating time reflects and quantifies a reduction in the stiffness of the rock due to annealing. The internal friction of the samples first increases then decreases with reaction time, reflecting defect annealing, but this was balanced against grain boundary dissolution apparently driven by condensation of steam in the confined grain-boundary environment. This suggests an increase in the boiling point under confinement leading to dissolution, increased porosity and widening of the grain boundaries. In addition, comparison of small-angle X-ray and neutron scattering results suggests that it is inappropriate to assume that pores are empty for quantitative analysis of typical small-angle scattering samples.

58 GEOSCIENCES↗

Comparison of atmospheric radionuclide dispersion models for a risk-informed consequence-driven advanced reactor licensing framework

Current nuclear facility emergency planning zones (EPZs) are based on outdated distance-based criteria, predating comprehensive dose and risk-informed frameworks. Recent advancements in simulation tools have permitted the development of site-specific, dose, and risk-based consequence-driven assessment frameworks. This study investigated the computation of advanced reactor (AR) EPZs using two atmospheric dispersion models: a straight-line Gaussian plume model (GPM) and a semi-Lagrangian Particle in Cell (PIC). Two case studies were conducted: (1) benchmarking the NRC SOARCA study for the Peach Bottom Nuclear Generating Station and (2) analyzing an advanced INL Heat Pipe Design A microreactor's end-of-cycle inventory. The dose criteria for both cases were 10 mSv at mean weather conditions and 50 mSv at 95th percentile weather conditions at 96 h post-release. Results demonstrated that GPM and PIC estimated similar mean peak dose levels for large boiling water reactors in the farfield case, placing EPZ limits beyond current regulations. For ARs with source terms remaining in the nearfield, PIC modeling without specific nearfield considerations could result in excessively high doses and inaccurate EPZ designations. PIC dispersion demonstrated an order of magnitude higher estimate of nearfield inhalation dose contribution when compared to GPM results. Furthermore, both models significantly reduced EPZ sizing within the nearfield. Thus, reductions in the AR source term may eliminate the need for a separate EPZ.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗