Challenges and Opportunities of Modeling Biomass Gasification in Aspen Plus: A Review

Aspen Plus has become one of the most common process simulation tools for both academia and industrial applications. In the last decade, the number of the papers on Aspen Plus modeling of biomass gasification has significantly increased. This review focuses on recent developments and studies on modeling biomass gasification in Aspen Plus including key aspects such as tar formation and model validation. Accordingly, challenges in modeling due to specific assumptions and limitations will be highlighted to provide a useful basis for researchers and end-users for further process modeling of biomass gasification in Aspen Plus.     

Numerical modeling of effect of slot on bubble motion in aluminum electrolytic process

A transient three-dimensional (3D) model was established to understand the bubble motion in an industrial electrolytic process. An anode with a new design was tested. It incorporates two slots that allow an efficient removal of gas bubbles. The electromagnetic fields were described by solving Maxwell's equations. The bubble movement was studied with two-way coupling Euler–Lagrange approach. The interplay of current density and bubble nucleation rate was included. The collision and coalescence of bubbles were considered. Random walk module was invoked for involving the chaotic effect of the turbulence. The numerical results were validated by experimental measurements. The results indicate that the current distribution and the bubble nucleation periodically change. Due to the slot, the bubble elimination heavily increases. The contribution of the slot to the bubble removal exceeds 50% in the case of three currents, and the promotion of the slot decays with increasing the current.     

Efficient model selection for real-time adaptive cold start strategy of a fuel cell system on vehicular applications

The PEMFC maximum power is greatly influenced by subfreezing temperature and degradation phenomena. Therefore, a dependable model is required to estimate the power with respect to the variation of the operating conditions and state of health. Semi-empirical models are potent tools in this regard. Nonetheless, there is not much information about their cold environment reliability. This paper comprehensively compares the performance of some models (already tested in normal ambient temperature) in subfreezing condition to introduce the most reliable one for PEMFC cold start-up application. Firstly, seven models are compared regarding voltage losses and precision. Subsequently, the three most dependable ones are selected and experimentally compared at sub-zero temperature in terms of polarization curve estimation for three PEMFCs with different degradation levels. The results of this study indicate that the model introduced by Amphlett et al. has a superior performance compared to other ones regarding the characteristic's estimation in below-zero temperature.     

热压烧结制备Cu/FeCoCr复合材料的显微组织及热物理性能

利用相图计算的CALPHAD方法和超音雾化制粉技术,在CuFeCoCr体系中设计并制备了一系列微米级复合粉体。通过热压烧结方法在烧结温度为950℃,烧结压力为45 MPa的工艺条件下成功获得块体复合材料。研究了块体复合材料中Cu含量对显微组织,热导率,热膨胀系数以及显微硬度的影响。结果表明:CuFeCoCr块体复合材料均由fcc富铜相和fcc富铁钴铬相组成。该系列复合材料经600℃时效处理8 h后,其热膨胀系数变化范围为5.83×10-6~10.61×10-6 K-1,热导率变化范围为42.17~107.53 W·m-1·K-1。其中Cu55(Fe0.37Cr0.09Co0.54)45复合材料表现出良好的综合性能,即其热膨胀系数和热导率分别为9.08×10-6K-1和91.09 W·m-1·K-1,与电子封装半导体材料的热膨胀系数相匹配。     

A datamining approach to classify,select and predict the formation enthalpy for intermetallic compound hydrides

In this paper, two techniques of datamining tools were adopted, a principal component analysis (PCA) and artificial neural network (ANN). A PCA to classify, select and identify several combinations between transition element A and B (B = Ti, Zr, Hf, Sc, Y, La and Th) and ANN to predict ΔH for ternary hydrides. Based on the datasets selected from different works, a principal component analysis (PCA) has been applied to select, classify and identify around 76 possible combinations between transition metal elements A and B. The results showed that the clustering of combinations A-B are significantly influenced by the atomic parameters of element A, such atomic radius (R_A), Pauling's electronegativity (χ_A) and atomic electron density (Z_A/R_A³). From 76 combinations, 55 systems which have χ_A ≥ 1.5, Z_A/R_A³>1.28 and R_A < 1.46 Å are categorized as group 1. On the other hand, 21 systems which have χ_A < 1.5, Z_A/R_A³ < 1.28, and R_A > 1.46 Å are categorized as group 2. From the first group, 46 different combinations are identified and have a negative ΔH, within 18 well-known promising binary alloys of hydrogen storage.An (6-15-1) architecture of artificial neural network (ANN) has been developed to estimate the ΔH for the other ternary hydrides selected from different published works. The performance indices such as relative error, coefficient of determination (R²) and mean square error (MSE) were used to control the performance of obtained results. In addition to this, the ΔH obtained from ANN model were compared with those experimental data and theoretical results available in the literature.     

Assignment of inter-die signals in a simplified wiring model for die-stacking SiP designs

Compared with traditional flow in IC designs, the assignment of the inter-die signals between different dies is an important stage in a die-stacking SiP design. In this paper, given a tolerant spacing rule between two inter-die signals, the crossing constraint between two inter-die signals can be firstly defined for the bonding wires in a die-stacking SiP design with a simplified wiring model [7]. Furthermore, based on the connection constraint on any inter-die signal, the capacity constraint on any assigned pad on dies and the crossing constraint between two inter-die signals, an integer linear programming-based (ILP-based) approach is proposed to assign all the inter-die signals to minimize the total wirelength in a die-stacking SiP design. Compared with Lin’s two-stage approach [4] for some tested examples without a tolerant spacing distance between two inter-die signals in an Euclidean wiring model, the experimental results show that our proposed ILP-based approach increases 4.5% of CPU time and reduces 6.2% of total wirelength to assign all the inter-die signals on the average. Besides that, compared with Yan’s iterative approach [6] for some tested examples without a tolerant spacing distance between two inter-die signals in an Euclidean wiring model, the experimental results show that our proposed ILP-based approach uses reasonable CPU time to reduce 5.3% of total wirelength to assign all the inter-die signals on the average. Compared with Lin’s modified two-stage approach and Yan’s modified iterative approach for some dense tested examples with a tolerant spacing distance between two inter-die signals in a simplified wiring model [7], the experimental results show that Lin’s modified two-stage approach only achieves 95.9% of the assignment ratio on the average, Yan’s modified iterative approach only achieves 96.6% of the assignment ratio on the average and our proposed ILP-based approach uses reasonable CPU time to achieve 100% of the assignment ratio.     

Calculating the degree of degradation of the volatile solids in continuously operated bioreactors

Determining the degree of degradation is an important means of assessing the efficiency of biological processes. However, one should consider the fact that during degradation, the reference value, such as volume or the mass of total solids, is also subject to change. The assumption that the incoming and outgoing mass flows are identical is only possible for substrates with a high water content and hence, a low energy density. For substrates with a higher energy density, a correction by the gaseous mass flow is required, but usually its quantification is difficult, especially when examining full-scale plants or open systems. Based on the assumption that the mass of inorganic solids is constant during the process, a universally applicable equation has been developed, requiring only the input and output volatile solids concentrations for calculation.     

Quality improvement and backorder price discount under controllable lead time in an inventory model

The proposed study investigates a continuous review inventory model with order quantity, reorder point, backorder price discount, process quality, and lead time as decision variables. An investment function is used to improve the process quality. Two models are developed based on the probability distribution of lead time demand. The lead time demand follows a normal distribution in the first model and in the second model it does not follow any specific distribution but mean and standard deviation are known. We prove two lemmas to obtain optimal solutions for the normal distribution model and distribution free model. Finally, some numerical examples are given to illustrate the model.     

Elasto-Thermodiffusive Response in a Spherically Isotropic Hollow Sphere

The present work deals with the investigation of elasto-thermo diffusion interactions inside a spherically isotropic hollow sphere in the context of linear theory of generalized thermoelastic diffusion based on Green and Lindsay theory. The inner and outer boundaries of the body are free from stresses and are subjected to a time-dependent thermal shock and also the chemical shock. Laplace transform techniques are used to write the basic equations in the form of a vector matrix differential equations, which is then solved by the eigenvalue approach. The inversion of the transformed solution is carried out by applying the method of Bellman. The stress, temperature, mass concentration and chemical potential are computed and presented graphically. A comparative study of diffusive medium and thermoelastic medium is carried out, and it was seen that the effect of diffusion is significant on the stresses. A comparison of spherically isotropic body with isotropic body has also been presented, and a significant difference is observed.     

Designing e-Coordinator for improved teams collaboration in graduation projects

The work presented in this paper describes the design for Graduation Project eCoordination System in our department. The proposed eCoordinator provides effective team–team, supervisor–team and coordinator–supervisors–teams collaboration. eCoordinator is an attribute based framework that serves evolving an object oriented software system into agent oriented software system. Nowadays, agent-oriented software development technologies have evolved rapidly; it is emerging as a new paradigm for constructing intelligent more autonomous software systems. Therefore, several methodologies are available and it is difficult to determine the most appropriate methodology for specific project within different domains. This is especially occurs when re-engineering current object oriented software system. The case study is going to be rebuilding a virtual graduation project coordinator in Information Technology Department at King Saud University.