SEARCH · Engineering Papers
Results for “reactive flow”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Ab initio investigation of a hypersonic double cone experiment
This article presents a direct molecular simulation (DMS) of a reactive Mach 8.2 oxygen flow over a double cone geometry. The free stream conditions and article configuration generate a flow with thermal and chemical nonequilibrium, which are common attributes of hypersonic flight. This scenario was first studied experimentally at Calspan University of Buffalo Research Center’s test facility. DMS is a particle method that uses quantum mechanically derived interaction potentials to simulate molecular collisions within a flow field. Since these interaction potentials are the only modeling inputs used in the simulation, all flow features can solely be attributed to the ab initio potential energy surfaces. Hence, providing a comparison of a hypersonic ground test and numerical data anchored to quantum mechanics. The fundamental nature of DMS is leveraged to investigate molecular level mechanisms prevalent in the flow, and comparisons with lower fidelity simulations are presented to highlight the role of these first principles calculations as benchmark solutions.
Protective coatings with nanoscale multilayer architecture: current state and main trends
Binary systems (layers) and multicomponent layers with bilayer thicknesses varying from microns to a few nanometers are considered. A strong dependence of the microstructure formation on the deposition conditions (the magnitude of the bias potential, the flow of inert and reactive gases, the ion beam power (current density) supplied to the target) is found. General regularities in the change in the functional properties and structural state of the coatings are formulated. The conditions for the formation of a columnar structure and growth texture are noted; various mechanisms and their interpretation are proposed. Finally, the relationship among the size of nanograins, diffusion at the interphase boundary, and effects determining the physico-mechanical, tribological characteristics, as well as resistance to corrosion and oxidation, is shown.
Machine learning to discover mineral trapping signatures due to CO 2 injection
Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.
Rapid Mineral Precipitation During Shear Fracturing of Carbonate-Rich Shales
Target subsurface reservoirs for emerging low-carbon energy technologies and geologic carbon sequestration typically have low permeability and thus rely heavily on fluid transport through natural and induced fracture networks. Sustainable development of these systems requires deeper understanding of how geochemically mediated deformation impacts fracture microstructure and permeability evolution, particularly with respect to geochemical reactions between pore fluids and the host rock. Here, a series of triaxial direct shear experiments was designed to evaluate how fractures generated at subsurface conditions respond to penetration of reactive fluids with a focus on the role of mineral precipitation. Calcite-rich shale cores were directly sheared under 3.5 MPa confining pressure using BaCl 2 -rich solutions as a working fluid. Experiments were conducted within an X-ray computed tomography (xCT) scanner to capture 4-D evolution of fracture geometry and precipitate growth. Three shear tests evidenced nonuniform precipitation of barium carbonates (BaCO 3 ) along through-going fractures, where the extent of precipitation increased with increasing calcite content. Precipitates were strongly localized within fracture networks due to mineral, geochemical, and structural heterogeneities and generally concentrated in smaller apertures where rock:water ratios were highest. The combination of elevated fluid saturation and reactive surface area created in freshly activated fractures drove near-immediate mineral precipitation that led to an 80% permeability reduction and significant flow obstruction in the most reactive core. While most previous studies have focused on mixing-induced precipitation, this work demonstrates that fluid–rock interactions can trigger precipitation-induced permeability alterations that can initiate or mitigate risks associated with subsurface energy systems.
Dataset documenting reaction-induced changes to five fractured foamed wellbore cement cores during CO2 fluid flow
This dataset consists of reconstructed CT scans for four fractured foamed cement cores, generated in the lab using Portland Class H cement, and associated processed data. The cements were exposed to reactive brines, and CT scans were take at different time points through the experiment. The CT imaging allows for the tracking of dissolution-induced changes to fracture morphology, as well as alteration and dissolution in the cement matrix.
Limit cycle oscillations in the zonal-flow-catalyzed interactions of ion-temperature-gradient turbulence
Limit-cycle oscillations are studied for ion temperature gradient turbulence, which, in the absence of large diamagnetic (mean) shear flows, saturates through energy transfer from unstable modes to large-scale stable modes via zonal-flow intermediary modes. Oscillations of zonal flow and turbulence levels are strongly constrained by the reactive, largely non-dissipative character of the zonal flows. Since existing predator–prey models for observed oscillations in experiments do not include energy transfer through zonal flows to stable modes, low-order fluid models with this physics are constructed and investigated. A simple three-wave truncation produces low-amplitude zonal flows that slowly oscillate around a zero mean, with turbulence oscillations between coupled wavenumbers that exceed linear frequencies by orders of magnitude. This inconsistency with experimental observations is caused by the weak non-linear drive of zonal flows in three-wave systems and the lack of multiple-wavenumber turbulent interactions. A more comprehensive model that preserves multiple wavenumber interactions within the context of conservative zonal-flow-mediated energy transfer to stable modes accurately reflects observed dynamics when the phase between stable and unstable modes is occasionally randomized.
Sensitivity Analysis of Transient Critical Heat Flux by RIA Under High-Pressure Flow Boiling Conditions in TRTL
A reactivity-initiated accident (RIA) is a design-basis accident under which critical heat flux (CHF) is likely to be exceeded. The operational margin for RIAs is currently determined using steady-state CHF lookup tables, which provide conservative estimates relative to transient CHF phenomena. The Transient Reactor Test Loop (TRTL) facility at Oregon State University is capable of performing out-of-pile rapid heating experiments representative of a RIA at conditions representative of a pressurized water reactor (PWR). Here, to further our understanding of and ability to predict transient CHF under PWR conditions, we performed a sensitivity analysis on a RELAP5-3D model of the TRTL facility coupled to the RAVEN code framework to define a proposed experimental test matrix to be performed at the TRTL facility. We then implemented a flow boiling CHF correlation into RELAP5-3D and performed a secondary sensitivity analysis inspecting the impact of the built-in RELAP5-3D CHF and heat transfer multipliers on both the prediction of CHF and key safety parameters, such as peak cladding temperature and heat flux. The results show that the multiplier with the highest influence toward the prediction of CHF occurrence and the safety parameters is the transient CHF multiplier. Operational performance envelopes have been developed for each of the test matrix cases and will be used for validation once the experiments are performed. The TRTL facility is currently performing shakedown testing to verify system performance prior to proceeding with the experimental campaign. Restart testing results include pump curve restart testing, pressure tests, and heater rod thermocouple transients.
Impact of Boron-Containing Lubricant Additive on Three-Way Catalyst Reactivity and Physicochemical Properties
Boron-containing compounds are one of the lubricant additive options due to their suitable properties for additives and have been used as commercial lubricant additives. In the present study, the impact of a boron-containing lubricant oil additive, AR9100 (BR), on Pd/Rh-based three-way catalyst (TWC) performance is investigated, and the results are compared with the baseline no-additive (NA) case and the industry standard zinc dialkyl-dithiophosphate (ZDDP) results. Accelerated engine aging is performed using a genset to expose the catalysts to lubricant additives at high temperatures. All aged TWC samples are investigated for reactivity in a bench-flow reactor and characterized using a variety of analytical techniques. Compared with the no-additive case, the temperatures of 90% conversion (T 90 ) of NO, CO, C 3 H 6 , and C 3 H 8 for the ZDDP-aged TWC sample increased by 34, 30, 37, and 48 °C. However, the T 90 of all gas species for the BR-aged TWC sample are similar to the NA-aged TWC sample. Additionally, a significant decrease in water–gas shift reactivity and oxygen storage capacity is observed in the ZDDP-aged sample, but not in the BR-aged sample. Inductively coupled plasma-optical emission spectrometry (ICP-OES) analysis and electron probe microanalysis (EPMA) maps of accelerated engine aging samples show the presence of phosphorus and boron in ZDDP- and BR-aged TWC samples, respectively. However, no boron-related peaks are observed in the X-ray diffraction (XRD) pattern of the BR-aged TWC sample, which may exist in the form of an amorphous phase.
Mechanistic understanding of carbon mineralization in fracture systems using microfluidics
Carbon mineralization in mafic and ultramafic rocks presents an opportunity for permanent carbon storage in the Earth's subsurface. However, due to their lower permeability, pre-existing fracture networks are key for mineralization to occur. Therefore, to fully develop this technology, a mechanistic understanding of the mineralization behavior in fractures with the consideration of hydrodynamic components is required. We use high-pressure microfluidics to investigate key mechanisms influencing dissolution–precipitation in a fracture network. The experiments were conducted in micromodels made of natural rocks with a comb-shaped flow channel to mimic a fracture network. This enabled studying the effect of injection rate on coupled dissolution–precipitation in advection and diffusion-dominated flow paths. We used gypsum carbonation as an analog reaction to allow for realistic experimental time frames due to its rapid reaction kinetics. The experimental work is coupled with high-fidelity numerical simulations to enhance our understanding of the parameters affecting the mineralization reaction. Our results demonstrate the importance of flow rate on the rate and nature of the gypsum carbonation reaction revealing that higher flow rates enable deeper penetration of the mineral precipitation front into the dead-end channels. This is an important finding since for sustained mineralization in a fracture network, precipitation in dead-ends while still allowing for flowing fractures is critical. Detailed characterization of the precipitates showed that lower flow rates led to porous and loose precipitates in the form of aragonite while higher flow rates mimicked supersaturation behavior leading to the formation of calcite. The reactive transport simulations further demonstrated the significance of flow velocity in advection-dominated channels to influence the efficiency of carbon mineralization in diffusion-dominated channels, potentially clogging of dead-end channels. These findings highlight the need for coupling chemical, mechanical, and hydrodynamic processes to evaluate the nature and extent of carbon mineralization in fractured media critical for permanent storage in mafic and ultramafic formations. This research further highlights the need for more investigation in potential subsurface fracture generation techniques to aid carbon mineralization.
Visualization and analysis of coupling between plasmas self-organization and plasma-induced fluid circulation in 1 atm DC glows with liquid anode
The physical processes prevailing when plasma contacts liquid water are poorly understood; however, it is this very interaction that is the basis of new, exciting technologies for water purification, the treatment of cancer and disease and the production of new, high value chemical products. A chief impediment to widespread application of plasmas for the aforementioned applications is scale up and cost. Here we investigate plasma induced flows which facilitate transport of reactivity from the plasma to liquid water at rates much faster than diffusion. We find that this plasma induced motion varies depending on whether or not the plasma is self organized. The insight from this work paves the way to a better understanding of transport and ultimately informing plasma treatment technologies on how to best optimize the rate at which processes such as plasma based water purification occurs.
ERSAP: Toward Better NP Data-Stream Analytics With Flow-Based Programming
This paper presents an reactive, actor-model and FBP paradigm based framework that we develop to design data-stream processing applications for HEP and NP. This framework encourages a functional decomposition of the overall data processing application into small mono-functional artifacts. Artifacts that are easy to understand, develop, deploy and debug. The fact that these artifacts (actors) are programmatically independent they can be scaled and optimized independently, which is impossible to do for components of the monolithic application. One of the important advantages of this approach is fault tolerance where independent actors can come and go on the data-stream without forcing the entire application to crash. Furthermore, it also makes it is easy to locate the faulty actor in the data pipeline. Due the fact that the actors are loosely coupled, and that the data (inevitably) carries the context, they can run on heterogeneous environments, utilizing different accelerators. This paper describes the main design concepts of the framework and presents a ?proof of concept? application design and deployment results obtain processing on-beam calorimeter streaming data.
Impacts of irregularly-distributed acidified brine flow on geo-chemo-mechanical alteration in an artificial shale fracture under differential stress
The efficacy of geological carbon sequestration is reliant on the integrity of the caprock and its resistance to physical and chemical alteration. Caprocks with high abundance of reactive carbonates like calcite are susceptible to acid-promoted dissolution and can result in structural weakening. This work investigates the effect of acidified brine flow through an artificially fractured, high-carbonate (30 % by XRD) shale under differential compressive stress. Cylindrical samples were cut in half vertically and milled to create an artificial fracture with interlocking asperities and open channels. Samples were sheared with a single applied stress in a custom flow cell housed within an industrial CT scanner. Further, either acidic (pH 4) or reservoir-simulated (pH 9.5) brine was flowed through the artificial fracture for 7–8 days under reservoir pressure and room temperature. Model simulations indicate flow mainly occurred in open channels, with limited flow between overlapping asperities. Analysis of fracture surfaces by optical and scanning electron microscopy show increased surface alteration and roughness after exposure to pH 4 versus pH 9.5 brine indicating mineral dissolution/loss, and this effect is greater in areas that receive the highest brine flows. Similarly, surface analysis by scratch testing shows fracture toughness decreases more after exposure to acidic versus reservoir-simulated brine, with the greatest alteration in areas of highest acidic brine flows. Despite weakening, no shear slip occurred. Overall, the results indicate that acidified brine can result in significant physical and geomechanical alteration of irregular fracture surfaces in shale caprock, with greatest effects in preferential flow regions.
A Review of Lattice-Boltzmann Models Coupled with Geochemical Modeling Applied for Simulation of Advanced Waterflooding and Enhanced Oil Recovery Processes
To maintain economic profit and improve the oil production efficiency after the primary and secondary production phase, advanced waterflooding techniques such as low salinity waterflooding in carbonate reservoirs have been investigated in numerical simulations, laboratory experiments, and field pilot tests. Multiple underlying mechanisms have been proposed based on these studies, and they are still under debate. Various numerical modeling approaches are introduced, but there exists a lack of a pore-scale comprehensive modeling scheme to fully understand the processes. Lattice-Boltzmann method (LBM) is a type of numerical fluid flow modeling technique that shows capabilities and flexibilities in modeling pore-scale fluid flow to integrate physical–chemical processes within complex structures. The intrinsic feature of LBM makes it a promising framework for simulating advanced waterflooding due to its flexibility, accuracy, and parallel efficiency. LBM works either by itself for solving reactive transport problems or by coupling with a third-party reaction solver. This review mainly introduces the LBM fluid flow and reactive transport capabilities and the concept and modeling approaches to simulate advanced waterflooding techniques. Meanwhile, an evaluation of the coupled LBM models for enhanced oil recovery (EOR) simulations is discussed with future research challenges and directions concluded.
A review of spatial Markov models for predicting pre-asymptotic and anomalous transport in porous and fractured media
Heterogeneity across a broad range of scales in geologic porous media often manifests in observations of non-Fickian or anomalous transport. While traditional anomalous transport models can successfully make predictions in certain geological systems, increasing evidence suggests that assumptions relating to independent and identically distributed increments constrain where and when they can be reliably applied. A relatively novel model, the Spatial Markov model (SMM), relaxes the assumption of independence. The SMM belongs to the family of correlated continuous time random walks and has shown promise across a wide range of transport problems relevant to natural porous media. It has been successfully used to model conservative as well as more recently reactive transport in highly complex flows ranging from pore scales to much larger scales of interest in geology and subsurface hydrology. In this review paper we summarize its original development and provide a comprehensive review of its advances and applications as well as lay out a vision for its future development.
Steering the methanol steam reforming reactivity of intermetallic Cu–In compounds by redox activation: stability vs . formation of an intermetallic compound–oxide interface
To compare the inherent methanol steam reforming properties of intermetallic compounds and a corresponding intermetallic compound–oxide interface, we selected the Cu–In system as a model to correlate the stability limits, self-activation and redox activation properties with the catalytic performance. Three distinct intermetallic Cu–In compounds – Cu 7 In 3 , Cu 2 In and Cu 11 In 9 – were studied both in an untreated and redox-activated state resulting from alternating oxidation–reduction cycles. The stability of all studied intermetallic compounds during methanol steam reforming (MSR) operation is essentially independent of the initial stoichiometry and all accordingly resist substantial structural changes. The inherent activity under batch MSR conditions is highest for Cu 2 In, corroborating the results of a Cu 2 In/In 2 O 3 sample accessed through reactive metal–support interaction. Under flow MSR operation, Cu 7 In 3 displays considerable deactivation, while Cu 2 In and Cu 11 In 9 feature stable performance at simultaneously high CO 2 selectivity. Here, the missing significant self-activation is most evident in the operando thermogravimetric experiments, where no oxidation is detected for any of the intermetallic compounds. In situ X-ray diffraction allowed us to monitor the partial decomposition and redox activation of the Cu–In intermetallic compounds into Cu 0.9 In 0.1 /In 2 O 3 (from Cu 7 In 3 ), Cu 7 In 3 /In 2 O 3 (from Cu 2 In) and Cu 7 In 3 /Cu 0.9 In 0.1 /In 2 O 3 (from Cu 11 In 9 ) interfaces with superior MSR performance compared to the untreated samples. Although the catalytic profiles appear surprisingly similar, the latter interface with the highest indium content exhibits the least deactivation, which we explain by formation of stabilizing In 2 O 3 patches under MSR conditions.
Streaming Readout and Data-Stream Processing With ERSAP
With the exponential growth in the volume and complexity of data generated at high-energy physics and nuclear physics research facilities, there is an imperative demand for innovative strategies to process this data in real or near-real-time. Given the surge in the requirement for high-performance computing, it becomes pivotal to reassess the adaptability of current data processing architectures in integrating new technologies and managing streaming data. This paper introduces the ERSAP framework, a modern solution that synergizes flow-based programming with the reactive actor model, paving the way for distributed, reactive, and high performance in data stream processing applications. Additionally, we unveil a novel algorithm focused on time-based clustering and event identification in data streams. The efficacy of this approach is further exemplified through the data-stream processing outcomes obtained from the recent beam tests of the EIC prototype calorimeter at DESY.
Impact of Primary and Secondary ZDDP and Ionic Liquid as Lubricant Oil Additives on the Performance and Physicochemical Properties of Pd-Based Three-Way Catalysts
In the present study, two industry primary and secondary zinc dialkyldithiophosphate standards, ZDDP1 and ZDDP2, respectively, are evaluated for their impact on the performance of Pd-based three-way catalyst and bench-marked against two mixed lubricant additives formed from either ZDDP1 or ZDDP2 with a second-generation oil-miscible phosphoric-containing ionic liquid (IL). The three-way catalysts (TWCs) are exposed to the lubricant additives in an engine bench under four different scenarios: a base case with no additive (NA), ZDDP1, IL+ZDDP1, ZDDP2, and IL+ZDDP2. The engine-aged TWC samples are characterized through a variety of analytical techniques, including evaluation of catalyst reactivity in a bench-flow reactor. With respect to the water–gas shift reaction and the oxygen storage capacity, the ZDDP2- and IL+ZDDP2-aged TWC samples are more degraded than the ZDDP1- and IL+ZDDP1-aged TWC samples. X-ray diffraction (XRD) patterns indicate that phosphorus in the form of CePO4 was found to be present in the washcoat of all TWC samples, with the highest amount found in the ZDDP2-aged TWC sample. The results obtained from XRD are further confirmed by those from inductively coupled plasma-optical emission spectroscopy (ICP-OES), which show that more phosphorus is detected in the washcoat of ZDDP2- and IL+ZDDP2-aged TWC samples than in the ZDDP1- and IL+ZDDP1-aged TWC samples.