A detailed insight into the optimization of plate and frame heat exchanger design by comparing old and new generation metaheuristics algorithms

The voluminous utilization and application of plate and frame heat exchangers (PFHE) in many industries has accelerated the consumer and designer both to optimize exchanger total cost. Over the last few years, several old and new generation algorithms were employed and exploited to optimize PFHE cost. This study explores the application and performance of three new-generation algorithms Big Bang-Big Crunch (BBBC), Grey Wolf Optimizer (GWO), and Water Evaporation Optimization (WEO) in designing optimally PFHE. Besides, this study also compares the performance of three well-established old generations algorithms namely genetic algorithm (genetics and natural selection), particle swarm optimization (animals behaviour), and differential evolution (population-based) with the above three new algorithms in the optimization of PFHE.Seven design factors are chosen for PFHE optimization: exchanger length on hot and cold sides, height and thickness of fin, length of the fin-strip, fin frequency, and the number of hot side layers. The applicability of the suggested algorithms is assessed using a case study based on published research. Though DE performs the best in this study of design optimization concerning total cost and computational time, the three new-generation meta-heuristic algorithms BBBC, GWO, and WEO also provide the novel scope of application in heat exchanger design optimization and successfully finding the cost of the heat exchanger. According to this study, capital costs increase by 19.5% for BBBC, 24% for GWO, and 7.6% for GWO, but operational costs fall by 9.5% for BBBC and GWO when compared to the best performing algorithm (DE). On the other hand, WEO shows an increase of 32.6% in operational costs. Aside from that, a full analysis of the computing time for each algorithm is also provided. The DE has the quickest run time of 0.09 ?s, while the PSO takes the longest at 33.97 ?s. The rest of the algorithms have nearly identical values. As a result, a good comparison is established in this study, offering an excellent platform for designers and customers to make selections. Additionally, the three new generations algorithms mentioned here were not used earlier for optimization of PFHE and the comparative study illustrates that each of them possesses eat potential for cost optimization and also solving other complex problems.     

微波/电热板组合消解-电感耦合等离子体质谱(ICP-MS)法测定土壤中重金属元素

为提高土壤检测的重金属得率,采用了微波消解/电热板组合预处理-电感耦合等离子体质谱法(ICP-MS)测定土壤重金属含量。分析了硝酸(HNO3)、氢氟酸(HF)、高氯酸(HClO4)和盐酸(HCl)组合消解液及赶酸温度对土壤预处理影响。结果显示：在硝酸和盐酸混合消解液中,硝酸占比越高,铬(Cr)、钴(Co)、铜(Cu)、镉(Cd)得率更高;消解液体系中加入氢氟酸可使消解更加彻底,提高铬与铜的得率。最优预处理消解条件为硝酸 6ml+ 氢氟酸 2ml消解液组合进行微波消解,1ml 高氯酸于155℃电热板上赶酸。经土壤标准样品GBW07401(GSS-1)和GBW07452(GSS-23)实际应用,预处理条件优化后测试准确度和稳定性均显著提高。此外使用元素铑(Rh)作为内标物时,其方法稳定性和准确性高于内标物钪(Sc)和锗(Ge)。可为相关国家土壤重金属测定标准的修制订提供方法学参考。     

碳酸氢钠浸提-连续流动分析法测定园艺植物堆肥中的有效磷

为了解堆肥中有效磷供应状况,采用碳酸氢钠浸提-连续流动分析法测定园艺植物堆肥中有效磷的含量。通过对样品前处理条件、仪器参数进行优化,确定了提取时间45 min,料液比1∶60,吸样时间35 s,清洗时间60 s,去离子水作为基线液。标准曲线的线性关系良好,相关系数大于0.999,精密度好;检出限为0.008 mg/L;与手动法相比,连续流动分析法自动化程度高,而且对环境和人均友好。     

Raney Ni催化生物基糠醛还原胺化合成糠胺

生物质衍生物糠醛还原胺化是合成糠胺的一种有效方法。本文以糠醛为原料、氨水为氨源,使用商业Raney Ni催化糠醛还原胺化合成糠胺,考察了氢压、温度、n(糠醛)/n(氨水)、溶剂、催化剂用量等条件对反应的影响。实验结果表明：在1,4-二氧六环溶剂中,0.03 g Raney Ni、n(糠醛)/n(氨水)=1/2、130 ℃、2.0 MPa H₂条件下反应3 h,糠醛转化率100%,糠胺选择性96.3%。与传统方法相比,该工艺实现了非贵金属催化剂作用下高选择性反应,具有操作简单、低成本、收率高等优点。      

基于混合离散粒子群算法的MPRM电路延时和面积综合优化

Polarity optimization for mixed polarity Reed-Muller(MPRM) circuits is a combinatorial issue.Based on the study on discrete particle swarm optimization(DPSO) and mixed polarity,the corresponding relation between particle and mixed polarity is established,and the delay-area trade-off of large-scale MPRM circuits is proposed. Firstly,mutation operation and elitist strategy in genetic algorithm are incorporated into DPSO to further develop a hybrid DPSO(HDPSO).Then the best polarity for delay and area trade-off is searched for large-scale MPRM circuits by combining the HDPSO and a delay estimation model.Finally,the proposed algorithm is testified by MCNC Benchmarks.Experimental results show that HDPSO achieves a better convergence than DPSO in terms of search capability for large-scale MPRM circuits.     

Einfluß der Sensor-Zeitkonstanten auf die Auswertbarkeit von Ta-Daten

All temperature sensors have a finitely time constant. The influence of the sensor time constant gt_s on the results of kinetic evaluation is demonstrated at four reaction types. The ignorance of the sensor indolence gives incorrect activation parameters. Therefore the determination of _s is necessary.For the estimation of parameters the nonlinear evaluation program TA-kin was used. With its help it is possible to find the real parameters, also when _s=32 s, if the real _s-value was entered.

     

Optimization of Vacuum-Microwave-Assisted Extraction of Natural Polyphenols and Flavonoids from Raw Solid Waste of the Orange Juice Producing Industry at Industrial Scale

Orange pomace (OP) is a solid waste produced in bulk as a byproduct of the orange juice industry and accounts for approximately 50% of the quantity of the fruits processed into juice. In numerous literature references there is information about diverse uses of orange pomace for the production of high-added-value products including production of natural antioxidant and antimicrobial extracts rich in polyphenols and flavonoids which can substitute the hazardous chemical antioxidants/antimicrobials used in agro-food and cosmetics sectors. In this work and for the first time, according to our knowledge, the eco-friendly aqueous vacuum microwave assisted extraction of orange pomace was investigated and optimized at real industrial scale in order to produce aqueous antioxidant/antimicrobial extracts. A Response Surface Optimization methodology with a multipoint historical data experimental design was employed to obtain the optimal values of the process parameters in order to achieve the maximum rates of extraction of OP total polyphenols and/or total flavonoids for economically optimum production at industrial scale. The three factors used for the optimization were: (a) microwave power (b) water to raw pomace ratio and (c) extraction time. Moreover, the effectiveness and statistical soundness of the derived cubic polynomial predictive models were verified by ANOVA.     

Impact of Collection Volume and DNA Extraction Method on the Detection of Biomarkers and HPV DNA in First-Void Urine

The potential of first-void (FV) urine as a non-invasive liquid biopsy for detection of human papillomavirus (HPV) DNA and other biomarkers has been increasingly recognized over the past decade. In this study, we investigated whether the volume of this initial urine stream has an impact on the analytical performance of biomarkers. In parallel, we evaluated different DNA extraction protocols and introduced an internal control in the urine preservative. Twenty-five women, diagnosed with high-risk HPV, provided three home-collected FV urine samples using three FV urine collection devices (Colli-Pee) with collector tubes that differ in volume (4, 10, 20 mL). Each collector tube was prefilled with Urine Conservation Medium spiked with phocine herpesvirus 1 (PhHV-1) DNA as internal control. Five different DNA extraction protocols were compared, followed by PCR for GAPDH and PhHV-1 (qPCR), HPV DNA, and HBB (HPV-Risk Assay), and ACTB (methylation-specific qPCR). Results showed limited effects of collection volume on human and HPV DNA endpoints. In contrast, significant variations in yield for human endpoints were observed for different DNA extraction methods (p < 0.05). Additionally, the potential of PhHV-1 as internal control to monitor FV urine collection, storage, and processing was demonstrated.     

Statistical Optimization of Flavonoid and Antioxidant Recovery from Macerated Chinese and Malaysian Lotus Root (Nelumbo nucifera) Using Response Surface Methodology

In this study, the combination of parameters required for optimal extraction of anti-oxidative components from the Chinese lotus (CLR) and Malaysian lotus (MLR) roots were carefully investigated. Box–Behnken design was employed to optimize the pH (X₁: 2–3), extraction time (X₂: 0.5–1.5 h) and solvent-to-sample ratio (X₃: 20–40 mL/g) to obtain a high flavonoid yield with high % DPPH_sc free radical scavenging and Ferric-reducing power assay (FRAP). The analysis of variance clearly showed the significant contribution of quadratic model for all responses. The optimal conditions for both Chinese lotus (CLR) and Malaysian lotus (MLR) roots were obtained as: CLR: X₁ = 2.5; X₂ = 0.5 h; X₃ = 40 mL/g; MLR: X₁ = 2.4; X₂ = 0.5 h; X₃ = 40 mL/g. These optimum conditions gave (a) Total flavonoid content (TFC) of 0.599 mg PCE/g sample and 0.549 mg PCE/g sample, respectively; (b) % DPPH_sc of 48.36% and 29.11%, respectively; (c) FRAP value of 2.07 mM FeSO₄ and 1.89 mM FeSO₄, respectively. A close agreement between predicted and experimental values was found. The result obtained succinctly revealed that the Chinese lotus exhibited higher antioxidant and total flavonoid content when compared with the Malaysia lotus root at optimum extraction condition.