Recent Submissions

  • An experimental study of inaccessible pore volume on polymer flooding and its effect on oil recovery

    Swadesi, Boni; Saktika, Erdico Prasidya; Sanmurjana, Mahruri; Siregar, Septoratno; Rini, Dyah (AIP Publishing, 2020-07-08) [Conference Paper]
    Polymer flooding is one of the methods to improve sweep efficiency and reduce water mobility when water channeling takes place in an oil reservoir. Theoretically, if the polymer viscosity increases, the mobility ratio decreases. Thus, the oil sweep becomes more efficient while the Recovery Factor (RF) becomes higher. However, there is a phenomenon in which polymer with higher viscosity does not always improve oil recovery. One of the factors that influence this phenomenon is the existence of Inaccessible Pore Volume (IPV), so this study is needed to determine the relationship between polymer rheology and the amount of IPV. Two commercial polymers with the same concentration, FP3630S and ChemEOR, were done by rheology testing and injected into several sandstone Berea cores. The effluents of salt tracer (potassium chloride) and polymer flood were collected, and their concentrations were measured using atomic absorption spectroscopy (AAS) and UV-Vis spectrometry, respectively. The determination of IPV is based on the trailing edge method. Based on Rheology test in the same concentration, polymer ChemEOR has a higher viscosity, but from the Coreflood test, ChemEOR has smaller oil recovery than FP3630S. The IPV of ChemEOR and FP3630S were 34 % and 28%, respectively. The size of IPV of a polymer is influenced by the ability of the polymer to increase viscosity, so that the greater the value of the viscosity given, the greater the value of IPV from the polymer. The FP3630S polymer can reach larger rock pores even though in terms of the water-oil mobility ratio is smaller than ChemEOR. With a smaller IPV, the result proves that FP3630 polymer displays an increase of oil recovery compared to ChemEOR polymer.
  • Numerical Investigation of Solute Transport in Fractured Porous Media Using the Discrete Fracture Model.

    El-Amin, Mohamed F.; Kou, Jisheng; Sun, Shuyu (Computational Science – ICCS 2020, Springer International Publishing, 2020-07-02) [Conference Paper]
    In this paper, we investigate flow with solute transport in fractured porous media. The system of the governing equations consists of the continuity equation, Darcy’s law, and concentration equation. A discrete-fracture model (DFM) has been developed to describe the problem under consideration. The multiscale time-splitting method was used to handle different sizes of time-step for different physics, such as pressure and concentration. Some numerical examples are presented to show the efficiency of the multi-scale time-splitting approach.
  • Feasibility of utilizing smart-phone cameras for seismic structural damage detection

    Alzughaibi, Ahmed A.; Ibrahim, Ahmed M.; Na, Yunsu; El-Tawil, Sherif; Eltawil, Ahmed (IEEE, 2020-06-30) [Conference Paper]
    When major natural disasters hit dense metropolitan areas, inspection is typically conducted by teams of engineers tasked with labeling buildings according to their damage state: safe, needs further evaluation, or unsafe. The physical inspection process can take from several days to weeks to be completed. Automated assessment is an attractive alternative to manual inspection but requires deploying a dense network of sensors at the granularity of each structure. Such a network may seem impractical with respect to cost or deployment time. However, with the advent of the Internet of Things (IoT) era, a massive network of citizen-owned smart devices such as tablets and smart-phones that contain vibration and vision sensors is already readily available and deployed. While prior work focused on using smart-phones to providing early warning, we focus specifically on utilizing smart-phone video capture to directly assess the structural health of buildings post event, thus providing emergency personnel with immediate actionable information regarding the state of the building. The fact that smart phone cameras are already located inside a given building makes the proposed solution insensitive to weather conditions and visibility range and does not require an off-structure reference point. Experimental results using shake tables show that the proposed technique can achieve sub-millimeter accuracy demonstrating its suitability for structural health monitoring applications.
  • Solving Acoustic Boundary Integral Equations Using High Performance Tile Low-Rank LU Factorization

    Al-Harthi, Noha A.; Alomairy, Rabab M.; Akbudak, Kadir; Chen, Rui; Ltaief, Hatem; Bagci, Hakan; Keyes, David E. (High Performance Computing, Springer International Publishing, 2020-06-18) [Conference Paper]
    We design and develop a new high performance implementation of a fast direct LU-based solver using low-rank approximations on massively parallel systems. The LU factorization is the most time-consuming step in solving systems of linear equations in the context of analyzing acoustic scattering from large 3D objects. The matrix equation is obtained by discretizing the boundary integral of the exterior Helmholtz problem using a higher-order Nyström scheme. The main idea is to exploit the inherent data sparsity of the matrix operator by performing local tile-centric approximations while still capturing the most significant information. In particular, the proposed LU-based solver leverages the Tile Low-Rank (TLR) data compression format as implemented in the Hierarchical Computations on Manycore Architectures (HiCMA) library to decrease the complexity of “classical” dense direct solvers from cubic to quadratic order. We taskify the underlying boundary integral kernels to expose fine-grained computations. We then employ the dynamic runtime system StarPU to orchestrate the scheduling of computational tasks on shared and distributed-memory systems. The resulting asynchronous execution permits to compensate for the load imbalance due to the heterogeneous ranks, while mitigating the overhead of data motion. We assess the robustness of our TLR LU-based solver and study the qualitative impact when using different numerical accuracies. The new TLR LU factorization outperforms the state-of-the-art dense factorizations by up to an order of magnitude on various parallel systems, for analysis of scattering from large-scale 3D synthetic and real geometries.
  • Learning Rank-1 Diffractive Optics for Single-shot High Dynamic Range Imaging

    Sun, Qilin; Tseng, Ethan; Fu, Qiang; Heidrich, Wolfgang; Heide, Felix (IEEE, 2020-06-15) [Conference Paper]
    High-dynamic range (HDR) imaging is an essential imaging modality for a wide range of applications in uncontrolled environments, including autonomous driving, robotics, and mobile phone cameras. However, existing HDR techniques in commodity devices struggle with dynamic scenes due to multi-shot acquisition and post- processing time, e.g. mobile phone burst photography, making such approaches unsuitable for real-time applications. In this work, we propose a method for snapshot HDR imaging by learning an optical HDR encoding in a single image which maps saturated highlights into neighboring unsaturated areas using a diffractive optical element (DOE). We propose a novel rank-1 parameterization of the proposed DOE which avoids vast trainable parameters and keeps high frequencies' encoding compared with conventional end-to-end design methods. We further propose a reconstruction network tailored to this rank-1 parametrization for recovery of clipped information from the encoded measurements. The proposed end-to-end framework is validated through simulation and real-world experiments and improves the PSNR by more than 7 dB over state-of-the-art end-to-end designs.
  • A full waveform inversion scheme for automated salt velocity model building

    Dzulkefli, F. S.; Kalita, Mahesh; Xin, K.; Alkhalifah, Tariq Ali; Ghazali, A. R. (European Association of Geoscientists & Engineers, 2020-06-14) [Conference Paper]
    In area with the presence of complex large salt bodies results in a much more complicated and highly nonlinear inversion problem where we have multiple local minima with the possibility of having an ill-pose FWI problem. Current method typically pick the top salt, flood it and pick the bottom salt and include the manually developed salt in the initial velocity model. It requires a clear contrast boundary between the salt and the background sediments. This is not only time consuming but the manual interpretation is vulnerable to errors especially the bottom of the salt. An automatic velocity model building is a better alternative to manual interpretation and horizon picking. By applying FWI in two stages of model regularization namely, FWI+TV and flooding, we successfully implemented an automated velocity model building for salt body on SEAM 3D salt model. FWI+TV act as a penalty function to control the variation in the model while preserving the edges of the salt body and flooding smear the high velocity below the top of the salt across the region where there is a drop in the velocity with depth. The proposed method is more robust and less time consuming compared to the standard 'migrate-pick-flood' approach.
  • Benchmarking solvers for the one dimensional cubic nonlinear klein gordon equation on a single core

    Muite, B. K.; Aseeri, Samar (Springer International Publishing, 2020-06-08) [Conference Paper]
    To determine the best method for solving a numerical problem modeled by a partial differential equation, one should consider the discretization of the problem, the computational hardware used and the implementation of the software solution. In solving a scientific computing problem, the level of accuracy can also be important, with some numerical methods being efficient for low accuracy simulations, but others more efficient for high accuracy simulations. Very few high performance benchmarking efforts allow the computational scientist to easily measure such tradeoffs in order to obtain an accurate enough numerical solution at a low computational cost. These tradeoffs are examined in the numerical solution of the one dimensional Klein Gordon equation on single cores of an ARM CPU, an AMD x86-64 CPU, two Intel x86-64 CPUs and a NEC SX-ACE vector processor. The work focuses on comparing the speed and accuracy of several high order finite difference spatial discretizations using a conjugate gradient linear solver and a fast Fourier transform based spatial discretization. In addition implementations using second and fourth order timestepping are also included in the comparison. The work uses accuracy-efficiency frontiers to compare the effectiveness of five hardware platforms
  • Research on Image Classification Method Based on DCNN

    Ma, Chao; Xu, Shuo; Yi, Xianyong; Li, Linyi; Yu, Chenglong (IEEE, 2020-05-30) [Conference Paper]
    Image classification is a kind of image processing technology, which can recognize different things by the feature information given by pictures. With the rapid development of science and technology and people's higher and higher demand for quality of life, image automatic classification technology has been applied to various fields of development. When we classify the image, the traditional image classification method can not accurately grasp the internal relationship between the recognition objects, and the traditional method also has the limitation of the recognition object's feature expression because of the too high characteristic dimension of the data, so the experimental results are not ideal. In view of the above content, this paper proposes an image detection method based on convolutional neural network. The experimental algorithm mainly refers to deep learning and convolutional neural network. Different from the traditional image classification methods, the deep convolution neural network model can be used for feature learning and image classification at the same time. By improving the structure of each part of the experiment and optimizing the convolution neural network model, the over fitting phenomenon can be prevented, and then the accuracy of image detection can be improved. The experiment on cifar-10 database shows that the improved deep learning model of this method has achieved effective results in image detection.
  • Remote Sensing Image Recognition Method Based on Faster R-CNN

    Ma, Chao; Li, Jinzhao; Wang, Zecong; Yi, Xianyong; Li, Linyi (IEEE, 2020-05-30) [Conference Paper]
    This paper proposes a method for remote sensing image recognition based on Faster R-CNN. Using Faster R-CNN model and ZFNet as the basic network, experiments show that the accuracy rate of Architecture, Greenhouses and Paddy field recognition is 90.67%, 93.85%, 83.33%, and the average recognition accuracy reached 89.28%. At the same time, compared with the recognition results of recognition detection methods such as CNN and TT-RICNN, it was found that the proposed Faster R-CNN model has better recognition performance well, with good recognition detection accuracy.
  • Efficient locality-sensitive hashing over high-dimensional data streams

    Yang, Chengcheng; Deng, Dong; Shang, Shuo; Shao, Ling (IEEE, 2020-05-27) [Conference Paper]
    Approximate Nearest Neighbor (ANN) search in high-dimensional space is a fundamental task in many applications. Locality-Sensitive Hashing (LSH) is a well-known methodology to solve the ANN problem with theoretical guarantees and empirical performance. We observe that existing LSH-based approaches target at the problem of designing search optimized indexes, which require a number of separate indexes and high index maintenance overhead, and hence impractical for high-dimensional streaming data processing. In this paper, we present PDA-LSH, a novel and practical disk-based LSH index that can offer efficient support for both updates and searches. Experiments on real-world datasets show that our proposal outperforms the state-of-the-art schemes by up to 10× on update performance and up to 2× on search performance.
  • Computational Drug-target Interaction Prediction based on Graph Embedding and Graph Mining

    Thafar, Maha A.; Albaradie, Somayah; Olayan, Rawan S.; Ashoor, Haitham; Essack, Magbubah; Bajic, Vladimir B. (ACM, 2020-05-22) [Conference Paper]
    Identification of interactions of drugs and proteins is an essential step in the early stages of drug discovery and in finding new drug uses. Traditional experimental identification and validation of these interactions are still time-consuming, expensive, and do not have a high success rate. To improve this identification process, development of computational methods to predict and rank likely drug-target interactions (DTI) with minimum error rate would be of great help. In this work, we propose a computational method for (Drug-Target interaction prediction using Graph Embedding and graph Mining), DTiGEM. DTiGEM models identify novel DTIs as a link prediction problem in a heterogeneous graph constructed by integrating three networks, namely: drug-drug similarity, target-target similarity, and known DTIs. DTiGEM combines different techniques, including graph embeddings (e.g., node2vec), graph mining (e.g., path scores between drugs and targets), and machine learning (e.g., different classifiers). DTiGEM achieves improvement in the prediction performance compared to other state-of-the-art methods for computational prediction of DTIs on four benchmark datasets in terms of area under precision-recall curve (AUPR). Specifically, we demonstrate that based on the average AUPR score across all benchmark datasets, DTiGEM achieves the highest average AUPR value (0.831), thus reducing the prediction error by 22.4% relative to the second-best performing method in the comparison.
  • Room Temperature Operable Semiconducting Metal Oxide Chemi-Resistive NO2 Gas Sensor

    Vijjapu, Mani Teja; Surya, Sandeep Goud; Yuvaraja, Saravanan; Salama, Khaled N. (ECS Meeting Abstracts, The Electrochemical Society, 2020-05-12) [Abstract]
    The quest for the room temperature operable semiconducting metal oxide gas sensors has come to an end. We fabricated an InGaZnO based chemi-resistive gas sensor, which is remarkably sensitive and selective to NO2 gas. Conventional semiconducting metal oxide gas sensors are active at high temperatures or in presence of light, which makes them power-hungry. The fabricated sensor is room temperature operable and requires light only to regenerate the device after exposure. NO2 has adverse effects on human health at concentration as low as 2 ppm. The measured limit of detection of the sensor is 100 ppb. Comprehensive NO2 adsorption studies were performed using kelvin probe force microscopy (KPFM) and X-ray photoelectron spectroscopy (XPS). The detailed mechanism of sensing and reviving is proposed. The fabricated sensor is compatible with CMOS process and can be integrated with the CMOS circuitry to make compact sensing system.
  • Large Eddy Simulations of Supercritical and Transcritical Jet Flows Using Real Fluid Thermophysical Properties

    Ningegowda, B. M.; Rahantamialisoa, Faniry; Zembi, Jacopo; Pandal, Adrian; Im, Hong G.; Battistoni, Michele (SAE International, 2020-04-14) [Conference Paper]
    In order to understand supercritical jet flows further, well resolved large eddy simulations (LES) of a n-dodecane jet mixing with surrounding nitrogen are conducted. A real fluid thermodynamic model is used to account for the fuel compressibility and variable thermophysical properties due to the solubility of ambient gas and liquid jet using the cubic Peng-Robinson equation of state (PR-EOS). A molar averaged homogeneous mixing rule is used to calculate the mixing properties. The thermodynamic model is coupled with a pressure-based solver to simulate multispecies reacting flows. The numerical model is based on a second order accurate method implemented in the open source OpenFOAM-6 software. First, to evaluate the present numerical model for sprays, 1D advection and shock tube benchmark problems at supercritical conditions are shown. Second, a cryogenic nitrogen injection with a jet velocity of 4.9 m/s into a supercritical nitrogen environment at 4 MPa and room temperature is considered to carry out a grid resolution study, and the corresponding results are evaluated against experimental data of Mayer et al. Then, to assess the effects of thermophysical property variations due to mixing of two species, a high-pressure jet of n-dodecane at transcritical and supercritical temperatures at 200 m/s into high-pressure and high-temperature nitrogen environment is studied. Detailed analysis of the species dispersion and mixing are presented for various conditions. The present LES simulations of n-dodecane jets show massive shear forces and high hydrodynamic pressure fluctuations caused by the high-speed jet. The predicted results of flow and thermophysical properties are in close agreement with the available literature data.
  • Validation of Computational Models for Isobaric Combustion Engines

    Aljabri, Hammam H.; Babayev, Rafig; Liu, Xinlei; Badra, Jihad; Johansson, Bengt; Im, Hong G. (SAE International, 2020-04-14) [Conference Paper]
    The focus of this study is to aid the development of the isobaric combustion engine by investigating multiple injection strategies at moderately high pressures. A three-dimensional (3D) commercial computational fluid dynamics (CFD) code, CONVERGE, was used to conduct simulations. The validation of the isobaric combustion case was carried out through the use of a single injector with multiple injections. The computational simulations were matched to the experimental data using methods outlined in this paper for different multiple injection cases. A sensitivity analysis to understand the effects of different modeling components on the quantitative prediction was carried out. First, the effects of the kinetic mechanisms were assessed by employing different chemical mechanisms, and the results showed no significant difference in the conditions under consideration. Next, different liquid fuel properties were examined, and it was found that the physical properties of the fuels have a notable effect in terms of evaporation and atomization, which lead to a variation in the considered numerical case. The effect of thermodynamics properties was also investigated by testing different equations of state (EOS) such as ideal gas, Redlich-Kwong, and Peng-Robinson. While the ideal gas model underpredicted the results, the other two EOS yielded similar and good predictions of the experimental data. The effects of different heat transfer models and the number of spray parcels were also found to be insignificant. Based on the sensitivity study, general guidance on different parameters to be used for isobaric combustion simulation was achieved.
  • Studying Ignition Delay Time of Lubricant Oil Mixed with Alcohols, Water and Toluene in IQT and CVCC

    Maharjan, Sumit; Elbaz, Ayman M.; Mitsudharmadi, Hatsari; Roberts, William L. (SAE International, 2020-04-14) [Conference Paper]
    The auto-ignition of liquid fuel and lubricant oil droplets is considered as one of the possible sources of pre-ignition. Researchers are continually finding new ways to form advanced lubricant oil by changing its composition and varying different oil additives to prevent the occurrence of this event. This study investigates additives for lubricants to suppress its auto-ignition tendency. Three sets of mixtures were prepared. The first set of mixtures were prepared by adding different alcohols namely ethanol, and methanol to the commercial lubricant oil (SAE 15W-40) in ratio of 1-5 % by vol The second set of mixtures were prepared by mixing SAE 15W-40 with aforementioned alcohols (1 % vol.) and H2O (1 % vol.). Lastly, the third set of mixtures were prepared by adding toluene to SAE 15W-40 in (1 %-5% by vol.). Two experimental setups were used in the current work. An Ignition Quality Tester (IQT) was used to investigate the mixtures' ignition delay time (IDT) following standard ASTM D6890 procedure, and a larger constant volume combustion chamber (CVCC) was used to investigate the combustion characteristics of a suspended single oil droplet. In the CVCC chamber, the droplet was ignited in an atmosphere of air at 300 C and pressure ranging from 4 bar-22 bar at 6 bar interval pressures. IDT of lubricant oil was considered as the base IDT, which was compared to those of other mixtures. Addition of alcohols and water in lubricant oil showed a significant increase in IDT compared to toluene addition. On the contrary, the addition of toluene resulted in a decrease in IDT. Among the alcohols, methanol addition showed higher IDT than ethanol addition. Alcohols increased the IDT effectively only beyond the addition of > 4 % by vol.
  • Effect of Pre-Chamber Enrichment on Lean Burn Pre-Chamber Spark Ignition Combustion Concept with a Narrow-Throat Geometry

    Hlaing, Ponnya; Echeverri Marquez, Manuel; Singh, Eshan; Almatrafi, Fahad; Cenker, Emre; Ben Houidi, Moez; Johansson, Bengt (SAE International, 2020-04-14) [Conference Paper]
    Pre-chamber spark ignition (PCSI) combustion is an emerging lean-burn combustion mode capable of extending the lean operation limit of an engine. The favorable characteristic of short combustion duration at the lean condition of PCSI results in high efficiencies compared to conventional spark ignition combustion. Since the engine operation is typically lean, PCSI can significantly reduce engine-out NOx emissions while maintaining short combustion durations. In this study, experiments were conducted on a heavy-duty engine at lean conditions at mid to low load. Two major studies were performed. In the first study, the total fuel energy input to the engine was fixed while the intake pressure was varied, resulting in varying the global excess air ratio. In the second study, the intake pressure was fixed while the amount of fuel was changed to alter the global excess air ratio. At each global excess air ratio, the fuel injection to the pre-chamber was varied parametrically to assess the effect of pre-chamber enrichment on engine operating characteristics. Multi-chamber heat release analysis was performed to present the pre-chamber and main chamber heat release characteristics separately. The discharge coefficient of the pre-chamber nozzles was determined by the model calibration to match the pre-chamber and main chamber pressure traces in the GT Power software. The analyzed data reveals a two-stage combustion mechanism in the main chamber where the latter stage is thought to be contributing to the bulk ignition of the main chamber charge. The pre-chamber heat release is correlated to the mixture strength of the pre-chamber, which affects the phasing of the pre-chamber combustion and the initial heat release in the main chamber. As the global excess air ratio becomes lean, the combustion efficiency deteriorates with high HC and CO emissions, while NOx emission declines significantly. The resulting heat release data is presented alongside the engine-out specific emissions.
  • Isobaric Combustion at a Low Compression Ratio

    Dyuisenakhmetov, Aibolat; Goyal, Harsh; Ben Houidi, Moez; Babayev, Rafig; Badra, Jihad; Johansson, Bengt (SAE International, 2020-04-14) [Conference Paper]
    In a previous study, it was shown that isobaric combustion cycle, achieved by multiple injection strategy, is more favorable than conventional diesel cycle for the double compression expansion engine (DCEE) concept. In spite of lower effective expansion ratio, the indicated efficiencies of isobaric cycles were approximately equal to those of a conventional diesel cycle. Isobaric cycles had lower heat transfer losses and higher exhaust losses which are advantageous for DCEE since additional exhaust energy can be converted into useful work in the expander. In this study, the performance of low-pressure isobaric combustion (IsoL) and high-pressure isobaric combustion (IsoH) in terms of gross indicated efficiency, energy flow distribution and engine-out emissions is compared to the conventional diesel combustion (CDC) but at a relatively lower compression ratio of 11.5. The experiments are conducted in a Volvo D13C500 single-cylinder heavy-duty engine using standard EU diesel fuel. The current study consists of two sets of experiments. In the first set, the effect of exhaust gas recirculation (EGR) is studied at different combustion modes using the same air-fuel ratio obtained from the preceding work. In the second set of experiments, different injection strategies are investigated for IsoL and IsoH combustion at constant and varying load conditions. From the results, it is found that isobaric combustion has similar or higher gross indicated efficiency than those of CDC. The exhaust losses are higher while the heat transfer losses are lower than CDC, which could be beneficial for DCEE concept. For isobaric cases, the NOx emissions were lower with higher uHC/CO/Soot emissions compared to CDC. From the injection strategy study, it was found that the gross indicated efficiency is highest with three injections i.e. at medium load. The efficiency is lower for both low and high load conditions due to increased exhaust and heat transfer losses, respectively. Also, the gross indicated efficiency is largely unchanged when more than one injection event is executed; however the IsoL yields higher overall emissions as compared to IsoH combustion.
  • Isobaric Combustion for High Efficiency in an Optical Diesel Engine

    Nyrenstedt, Gustav; AlRamadan, Abdullah; Tang, Qinglong; Badra, Jihad; Cenker, Emre; Ben Houidi, Moez; Johansson, Bengt (SAE International, 2020-04-14) [Conference Paper]
    Isobaric combustion has been proven a promising strategy for high efficiency as well as low nitrogen oxides emissions, particularly in heavy-duty Diesel engines. Previous single-cylinder research engine experiments have, however, shown high soot levels when operating isobaric combustion. The combustion itself and the emissions formation with this combustion mode are not well understood due to the complexity of multiple injections strategy. Therefore, experiments with an equivalent heavy-duty Diesel optical engine were performed in this study. Three different cases were compared, an isochoric heat release case and two isobaric heat release cases. One of the isobaric cases was boosted to reach the maximum in-cylinder pressure of the isochoric one. The second isobaric case kept the same boost levels as the isochoric case. Results showed that in the isobaric cases, liquid fuel was injected into burning gases. This resulted in shorter ignition delays and thus a poor mixing level. The lack of fuel/air mixing was clearly the main contributor to the high soot emissions observed in isobaric combustion. The lower heat losses of the isobaric strategy were further explained by tracking the chemiluminescence. Unlike a long single injection, multiple injections helped to contain the hot gases away from the walls. However, the opposite effects were also found from the high thermal radiation caused by the extensive soot formation. High-pressure fluctuations from the rapid heat release of the isochoric case were further seen. Finally, better mixing for improved air utilization was deemed needed when utilizing isobaric heat release.
  • Combustion System Optimization of a Light-Duty GCI Engine Using CFD and Machine Learning

    Badra, Jihad; KHALED, Fethi; Sim, Jaeheon; Pei, Yuanjiang; Viollet, Yoann; Pal, Pinaki; Futterer, Carsten; Brenner, Mattia; Som, Sibendu; farooq, aamir; Chang, Junseok (SAE International, 2020-04-14) [Conference Paper]
    In this study, the combustion system of a light-duty compression ignition engine running on a market gasoline fuel with Research Octane Number (RON) of 91 was optimized using computational fluid dynamics (CFD) and Machine Learning (ML). This work was focused on optimizing the piston bowl geometry at two compression ratios (CR) (17 and 18:1) and this exercise was carried out at full-load conditions (20 bar indicated mean effective pressure, IMEP). First, a limited manual piston design optimization was performed for CR 17:1, where a couple of pistons were designed and tested. Thereafter, a CFD design of experiments (DoE) optimization was performed where CAESES, a commercial software tool, was used to automatically perturb key bowl design parameters and CONVERGE software was utilized to perform the CFD simulations. At each compression ratio, 128 piston bowl designs were evaluated. Subsequently, a Machine Learning-Grid Gradient Algorithm (ML-GGA) approach was developed to further optimize the piston bowl design. This extensive optimization exercise yielded significant improvements in the engine performance and emissions compared to the baseline piston bowl designs. Up to 15% savings in indicated specific fuel consumption (ISFC) were obtained. Similarly, the optimized piston bowl geometries produced significantly lower emissions compared to the baseline. Emissions reductions up to 90% were obtained from this optimization exercise. The performances of the optimized piston bowl geometries were further validated at different operating conditions at the high-load point and at part-load conditions (6 bar IMEP) and compared with those of the baseline designs. The dependence of the engine performance on the piston bowl geometry at part-loads was lower than that at high-loads because injections normally occurred earlier (-60 to-20 CAD after top dead center (aTDC)) where minimal interactions between the spray and piston were anticipated. The interactions between late injections (-3 to 3 CAD aTDC) and piston geometry at high-loads significantly affected, fuel-air mixing, droplet breakup, combustion and emissions. It was also observed that heat losses, dictated by the interactions between the flame and piston surface, significantly affected the performance of the engine.
  • On Maximizing Argon Engines' Performance via Subzero Intake Temperatures in HCCI Mode at High Compression Ratios

    Elkhazraji, Ali; Mohammed, Abdulrahman; Jan, Sufyan; Masurier, Jean-Baptiste; Dibble, Robert W.; Johansson, Bengt (SAE International, 2020-04-14) [Conference Paper]
    The improvement of the indicated thermal efficiency of an argon power cycle (replacing nitrogen with argon in the combustion reaction) is investigated in a CFR engine at high compression ratios in homogeneous charge compression ignition (HCCI) mode. The study combines the two effects that can increase the thermodynamic efficiency as predicted by the ideal Otto cycle: High specific heat ratio (provided by argon), and high compression ratios. However, since argon has relatively low heat capacity (at constant volume), it results in high in-cylinder temperatures, which in turn, leads to the occurrence of knock. Knock limits the feasible range of compression ratios and further increasing the compression ratio can cause serious damage to the engine due to the high pressure rise rate caused by advancing the combustion phasing. The technique proposed in this study in order to avoid intense knock of an argon cycle at high compression ratios is to cool the intake charge to subzero temperatures which leads to lower in-cylinder temperatures and hence, less possibility of having knock. The main variable in this study was the intake temperature which was investigated at 40.0 °C and-6.0 °C which corresponded to low and high compression ratios, respectively. Emission analysis shows that the low in-cylinder temperature of the cooled case led to less complete combustion, and so, lower combustion efficiency. Since nitrogen is replaced with argon, NOx was only formed in negligible amounts due to some nitrogen traces in the used gasses cylinders. Furthermore, the cooled charge required more work to be done in the gas exchange process due to the decrease in the intake pressure caused by cooling the intake which deteriorated the gas exchange efficiency. The heat losses factor was found to be the main parameter that dictated the improvement of the thermodynamic efficiency and it was found that the indicated thermal efficiency was deteriorated for the cooled case as a result of all the aforementioned factors. Although the values of the thermodynamic efficiency at high compression ratios did not meet the expectations based on the ideal Otto cycle due to the assumptions of the ideal cycle, the obtained values, in general, are relatively high.

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