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Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory
To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.
Structural properties of ferroelectric heterostructures using coherent bragg rod analysis
Abstract not provided
Removal of iodine (I- and IO3-) from aqueous solutions using CoAl and NiAl layered double hydroxides
The treatment of radioactive iodine released from nuclear power plants and radiological waste disposal sites is of great concern due to its high mobility and toxicity. In particular, iodide (I-) and iodate (IO3-) are the major iodine species of concern under various pHs and groundwater conditions. Herein, CoAl and NiAl layered double hydroxides (LDHs) were synthesized by a hydrothermal method and investigated to identify the removal mechanisms and efficiencies of both I- and IO3-. Both CoAl and NiAl LDHs exhibited rapid iodine removal processes within 20 min, following the pseudo-second-order model via ion-exchange with parent NO3- anion in the LDHs. The CoAl LDH’s maximum sorption capacities for I- and IO3- were about 1.67 and 2.16 mmol g-1, respectively, whereas for the NiAl LDH, these were about 2.10 and 2.26 mmol g-1, and they followed the Langmuir isotherm model. Interestingly, both the CoAl and NiAl LDHs showed a preferential ion-exchange affinity for IO3- over I-, which was attributed to the structural similarity of the IO3- and NO3- as well as new formation of secondary Co(or Ni)(IO3)2·2H2O phases. In addition, a desorption study indicated that the selectivity order was SO42- = IO3- = OH- > HCO3- > Cl- > NO3- = I- and demonstrated the higher retention of the IO3- than I- anion. This study provides insights into promising iodine sorbents and the different removal mechanisms of I- and IO3- using CoAl and NiAl LDHs.
The Drosophila hnRNP F/H Homolog Glorund Uses Two Distinct RNA-Binding Modes to Diversify Target Recognition
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Carbon capture test unit design and development using amine-based solid sorbent
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Scheduling double round-robin tournaments with divisional play using constraint programming
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Control co-design of commercial building chiller plant using Bayesian optimization
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Power grid simulation applications developed using the GridPACK™ high performance computing framework
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Toward a scalable robust security-constrained optimal power flow using a proximal projection bundle method
Robust security-constrained optimal power flow (rSCOPF) aims to find the worst-case contingencies of alternating current optimal power flow (ACOPF) in power systems. With the rise of GPU architectures on the upcoming supercomputer architectures, optimization algorithms that rely on sparse linear algebra and indefinite linear systems are becoming increasingly hard to solve efficiently (e.g. interior-point method). To address this we revisit a maximin optimization formulation of the rSCOPF and the single-level mixed-integer semidefinite programming (MISDP) reformulation, which is obtained by taking the Lagrangian relaxation of the inner minimization ACOPF problem. In this paper, we focus on the development of a proximal projection bundle method (PPBM) for solving continuous relaxation node subproblems of the MISDP problem, based primarily on the well-known alternating direction method of multipliers. Cutting planes reminiscent of bundle method ideas are also applied in coordination with updates of the proximal parameter. The cutting-plane method can generate a large number of linear inequalities, leading to a large scale but decomposable quadratic programming (QP) subproblem that is amenable to GPUs. We present the numerical results on the IEEE 30, 57, 118, and 300-bus systems by using our PBMM method. We discuss the main computational bottleneck of our method, which is the time taken to solve each iteration of a QP subproblem instance of the PPBM, and how GPU architectures can accelerate this solution process.
Fast robust power system dynamic state estimation using model transformation
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Enhancement of storage capacity of CO2 in megaporous saline aquifers using nanoparticle-stabilized CO2 foam
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Effect of Basic Residue on the Kinetics of Peptide Fragmentation Examined Using Surface-Induced Dissociation Combined with Resonant Ejection
In this work, resonant ejection coupled with surface-induced dissociation (SID) in a Fourier transform ion cyclotron resonance mass spectrometer is used to examine fragmentation kinetics of two singly protonated hexapeptides, RYGGFL and KYGGFL, containing the basic arginine residue and less basic lysine residue at the N-terminus. The kinetics of individual reaction channels at different collision energies are probed by applying a short ejection pulse (1 ms) in resonance with the cyclotron frequency of a selected fragment ion and varying the delay time between ion-surface collision and resonant ejection while keeping total reaction delay time constant. Rice-Ramsperger-Kassel-Marcus (RRKM) modeling of the experimental data provides accurate threshold energies and activation entropies of individual reaction channels. Substitution of arginine with less basic lysine has a pronounced effect on the observed fragmentation kinetics of several pathways, including the b2 ion formation, but has little or no effect on formation of the b5+H2O fragment ion. The combination of resonant ejection SID, time- and collision energy-resolved SID, and RRKM modeling of both types of experimental data provides a detailed mechanistic understanding of the primary dissociation pathways of complex gaseous ions.