Modeling advanced flash stripper for carbon dioxide capture using aqueous amines

The intensive energy use is the major obstacle to deployment of CO2 capture. Alternative stripper configurations is one of the most promising ways to reduce the energy consumption of CO2 regeneration and compression. The advanced flash stripper (AFS) proposed in this work provides the best energy performance among other alternatives. A systematic irreversibility analysis was performed instead of examining all the possible alternatives. The overhead condenser and the cross exchanger were identified the major sources of lost work that causes process inefficiencies. The AFS reduces the reboiler duty by 16% and the total equivalent work by 11% compared to the simple stripper using aqueous piperazine. The AFS was demonstrated in a 0.2 MW equivalent pilot plant and showed over 25% of heat duty reduction compared to previous campaigns, achieving 2.1 GJ/tonne CO2 of heat duty and 32 kJ/mol CO2 of total equivalent work. The proposed bypass control strategy was successfully demonstrated and minimized the reboiler duty. Approximate stripper models (ASM) were developed to generalize the effect of solvent properties on energy performance and guide solvent selections. High heat of absorption can increase partial pressure of CO2 at elevated temperature and has potential to reduce compression work and stripping steam heat. The optimum heat of absorption was quantified as 70–125 kJ/mol CO2 at various conditions, which is generally higher than existing amines with 60–80 kJ/mol. The energy performance of AFS is not sensitive to the heat of absorption. A techno-economic analysis with process optimization that minimizes the annualized regeneration cost was performed to demonstrate the profitability of the AFS. The AFS reduces the annualized regeneration cost by 13% and the major savings come from the reduction of the OPEX, which counts for over 70% of the regeneration cost. The compressor and the cross exchanger are the major components of the CAPEX. The optimum lean loading is around 0.22 mol CO2/mol alkalinity for PZ but is flat between 0.18 and 0.24 with less than 1% difference. The AFS was demonstrated as a flexible system that can be applied to a wide range of solvent properties and operating conditions while still maintaining remarkable energy performance. Further improvement of energy efficiency by process modifications is expected to be marginal. Increasing solvent capacity will give the most energy and cost reduction in the future.Chemical Engineerin

Apparatus for and method of removing acidic gas from a gaseous stream and regenerating an absorbent solution

An apparatus for and method of removing acidic gas from a gaseous stream and regenerating an aqueous solution allows for the recovery of waste heat of stripping steam and more economical regeneration of the aqueous solution. In at least one embodiment, one or more rich solvent bypasses combine with a rich solvent heat exchanger to recover waste heat. In another embodiment, the apparatus and method include one or more rich solvent bypasses and a heater positioned upstream of the stripper to more economically regenerate an aqueous solution.Board of Regents, University of Texas Syste

Conceptual models of dissolved carbon fluxes in a two-layer stratified lake: interannual typhoon responses under extreme climates

Extreme climates affect the seasonal and interannual patterns of carbon (C) distribution in lentic ecosystems due to the regimes of river inflow and thermal stratification. Typhoons rapidly load substantial amounts of terrestrial C into smaller subtropical lakes (i.e., Yuan-Yang Lake in Taiwan, hereafter referred to as YYL), renewing and mixing the water column. We developed a conceptual dissolved C model and hypothesized that allochthonous C loading and river inflow intrusion may affect the dissolved inorganic C (DIC) and dissolved organic C (DOC) distributions in a small subtropical lake under these extreme climates. A two-layer conceptual C model was developed to explore how the DIC and DOC fluxes respond to typhoon disturbances on seasonal and interannual timescales in YYL while simultaneously considering autochthonous processes such as algal photosynthesis, remineralization, and vertical transformation. To compare the temporal patterns of fluxes between typhoon years (2015–2016) and non-typhoon years (2017–2018), monthly field samples were obtained and their DIC, DOC, and chlorophyll a (Chl a) concentrations measured. The results demonstrated that net ecosystem production was 3.14 times higher in typhoon years than in non-typhoon years. These results suggested that a loading of allochthonous C was the most crucial driver of the temporal variation in C fluxes in typhoon years because of changes in physical and biochemical processes, such as photosynthesis, mineralization, and vertical transportation. However, the lowered vertical transportation rate shaped the seasonal C in non-typhoon years due to thermal stratification within this small subtropical lake.</p

A Novel Adaptive Elite-Based Particle Swarm Optimization Applied to VAR Optimization in Electric Power Systems

Particle swarm optimization (PSO) has been successfully applied to solve many practical engineering problems. However, more efficient strategies are needed to coordinate global and local searches in the solution space when the studied problem is extremely nonlinear and highly dimensional. This work proposes a novel adaptive elite-based PSO approach. The adaptive elite strategies involve the following two tasks: (1) appending the mean search to the original approach and (2) pruning/cloning particles. The mean search, leading to stable convergence, helps the iterative process coordinate between the global and local searches. The mean of the particles and standard deviation of the distances between pairs of particles are utilized to prune distant particles. The best particle is cloned and it replaces the pruned distant particles in the elite strategy. To evaluate the performance and generality of the proposed method, four benchmark functions were tested by traditional PSO, chaotic PSO, differential evolution, and genetic algorithm. Finally, a realistic loss minimization problem in an electric power system is studied to show the robustness of the proposed method

Intelligent PV Power Smoothing Control Using Probabilistic Fuzzy Neural Network with Asymmetric Membership Function

An intelligent PV power smoothing control using probabilistic fuzzy neural network with asymmetric membership function (PFNN-AMF) is proposed in this study. First, a photovoltaic (PV) power plant with a battery energy storage system (BESS) is introduced. The BESS consisted of a bidirectional DC/AC 3-phase inverter and LiFePO4 batteries. Then, the difference of the actual PV power and smoothed power is supplied by the BESS. Moreover, the network structure of the PFNN-AMF and its online learning algorithms are described in detail. Furthermore, the three-phase output currents of the PV power plant are converted to the dq-axis current components. The resulted q-axis current is the input of the PFNN-AMF power smoothing control, and the output is a smoothing PV power curve to achieve the effect of PV power smoothing. Comparing to the other smoothing methods, a minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the PV power smoothing control using PFNN-AMF. In addition, a personal computer- (PC-) based PV power plant emulator and BESS are built for the experimentation. From the experimental results of various irradiance variation conditions, the effectiveness of the proposed intelligent PV power smoothing control can be verified

Arsenic Exposure and Methylation Efficiency in Relation to Oxidative Stress in Semiconductor Workers

This study examined associations between oxidative stress and arsenic (As) exposure and methylation efficiency in semiconductor workers. An As-exposed group (n = 427) and a control group (n = 91) were included. The As-exposure group (n = 427) included 149 maintenance staff members and 278 production staff members representing high As exposure and low As exposure, respectively. The control group included 91 administrative staff members with no or minimal As exposure. An occupational exposure assessment was conducted to assess personal As exposure by measuring As concentrations in urine, hair, and fingernails of the subjects. Urinary As(III), As(V), monomethylarsonic (MMA), and dimethylarsinic acid (DMA) were quantified to assess an internal dose of inorganic As. Urinary 8-hydroxy-2’-deoxyguanosine (8-OHdG) and malondialdehyde (MDA) were measured to asses oxidative DNA damage and lipid peroxidation, respectively. As concentrations in urine, hair, and fingernails significantly increased (p \u3c 0.05) in the As-exposed group in comparison to the control group. Geometric mean urinary concentrations of As, 8-OHdG, and MDA in the As-exposed group significantly exceeded those in the control group. As exposure to As-exposed workers had increased concentrations of 8-OHdG in contrast to those in control subjects. Moreover, urinary 8-OHdG concentrations in the semiconductor workers were positively correlated with urinary total As metabolite (As(III) + As(V) + MMA + DMA) concentrations. Furthermore, urinary excretion of 8-OHdG concentrations in As-exposed workers were positively associated with urinary excretion of MMA concentrations and primary methylation index values (the ration of MMA/inorganic As). However, fingernail and hair samples did not perform as well as urinary samples to measure oxidative stress induced by As exposure. 8-OHdG could serve as a more reliable biomarker for assessing As methylation than MDA did. Occupational exposure to inorganic As was associated with increased oxidative stress among semiconductor workers

Simulation Modeling of Dual Warehouse System

Warehouse space allocation is a critical issue to be addressed in many firms, especially firms that have various types of products. Further, most of the owned warehouse has a limited capacity which leads to the usage of outsourcing policy for warehouse storage. In this case, a rented warehouse that has more flexibility in terms of capacity is used to store the products. Therefore, an optimal decision of warehouse configuration is required. The previous study proposed a two-stage stochastic optimization model for warehouse configuration and inventory policy for deteriorating items. Unfortunately, direct implementation of their proposed method in real case problems will incur high cost and takes up a lot of time. In this research, a simulation model is developed to monitor the real condition in the company as well as to ensure that the warehouse configuration is suitable to be implemented. A textile and apparel company is used as the study case. The result shows that simulation model can be used to monitor the real condition as well as to obtain the net profit when facing different demand possibility. Keywords: inventory control; real-time monitoring; system simulation; warehouse configuration; warehouse space allocatio