Application of Surrogate Based Optimisation in the Design of Automotive Body Structures

The rapid development of automotive industry requires manufacturers to continuously reduce the development cost and time and to enhance the product quality. Thus, modern automotive design pays more attention to using CAE analysis based optimisation techniques to drive the entire design flow. This thesis focuses on the optimisation design to improve the automotive crashworthiness and fatigue performances, aiming to enhance the optimisation efficiency, accuracy, reliability, and robustness etc. The detailed contents are as follows: (1) To excavate the potential of crash energy absorbers, the concept of functionally graded structure was introduced and multiobjective designs were implemented to this novel type of structures. First, note that the severe deformation takes place in the tubal corners, multi-cell tubes with a lateral thickness gradient were proposed to better enhance the crashworthiness. The results of crashworthiness analyses and optimisation showed that these functionally graded multi-cell tubes are preferable to a uniform multi-cell tube. Then, functionally graded foam filled tubes with different gradient patterns were analyzed and optimized subject to lateral impact and the results demonstrated that these structures can still behave better than uniform foam filled structures under lateral loading, which will broaden the application scope of functionally graded structures. Finally, dual functionally graded structures, i.e. functionally graded foam filled tubes with functionally graded thickness walls, were proposed and different combinations of gradients were compared. The results indicated that placing more material to tubal corners and the maximum density to the outmost layer are beneficial to achieve the best performance. (2) To make full use of training data, multiple ensembles of surrogate models were proposed to maximize the fatigue life of a truck cab, while the panel thicknesses were taken as design variables and the structural mass the constraint. Meanwhile, particle swarm optimisation was integrated with sequential quadratic programming to avoid the premature convergence. The results illustrated that the hybrid particle swarm optimisation and ensembles of surrogates enable to attain a more competent solution for fatigue optimisation. (3) As the conventional surrogate based optimisation largely depends on the number of initial sample data, sequential surrogate modeling was proposed to practical applications in automotive industry. (a) To maximize the fatigue life of spot-welded joints, an expected improvement based sequential surrogate modeling method was utilized. The results showed that by using this method the performance can be significantly improved with only a relatively small number of finite element analyses. (c) A multiojective sequential surrogate modeling method was proposed to address a multiobjective optimisation of a foam-filled double cylindrical structure. By adding the sequential points and updating the Kriging model adaptively, more accurate Pareto solutions are generated. (4) While various uncertainties are inevitably present in real-life optimisations, conventional deterministic optimisations could probably lead to the violation of constraints and the instability of performances. Therefore, nondeterministic optimisation methods were introduced to solve the automotive design problems. (a) A multiobjective reliability-based optimisation for design of a door was investigated. Based on analysis and design responses surface models, the structural mass was minimized and the vertical sag stiffness was maximized subjected to the probabilistic constraint. The results revealed that the Pareto frontier is divided into the sensitive region and insensitive region with respect to uncertainties, and the decision maker is recommended to select a solution from the insensitive region. Furthermore, the reduction of uncertainties can help improve the reliability but will increase the manufacturing cost, and the tradeoff between the reliability target and performance should be made. (b) A multiobjective uncertain optimisation of the foam-filled double cylindrical structure was conducted by considering randomness in the foam density and wall thicknesses. Multiobjective particle swarm optimisation and Monte Carlo simulation were integrated into the optimisation. The results proved that while the performances of the objectives are sacrificed slightly, the nondeterministic optimisation can enhance the robustness of the objectives and maintain the reliability of the constraint. (c) A multiobjective robust optimisation of the truck cab was performed by considering the uncertainty in material properties. The general version of dual response surface model, namely dual surrogate model, was proposed to approximate the means and standard deviations of the performances. Then, the multiobjective particle optimisation was used to generate the well-distributed Pareto frontier. Finally, a hybrid multi-criteria decision making model was proposed to select the best compromise solution considering both the fatigue performance and its robustness. During this PhD study, the following ideas are considered innovative: (1) Surrogate modeling and multiobjective optimisation were integrated to address the design problems of novel functionally graded structures, aiming to develop more advanced automotive energy absorbers. (2) The ensembles of surrogates and hybrid particle swarm optimisation were proposed for the design of a truck cab, which could make full use of training points and has a strong searching capacity. (3) Sequential surrogate modeling methods were introduced to several optimisation problems in the automotive industry so that the optimisations are less dependent on the number of initial training points and both the efficiency and accuracy are improved. (4) The surrogate based optimisation method was implemented to address various uncertainties in real life applications. Furthermore, a hybrid multi-criteria decision making model was proposed to make the best compromise between the performance and robustness

The Sediment Selectivity of Perinereis aibuhitensis Larvae: Active or Passive?

The selectivity of Perinereis aibuhitensis larvae on different sediment types was studied using an experimental behavioral device in the lab. There were six types of sediment with different organic matter content: 2.19, 2.30, 2.86, 3.25, 3.51, and 5.52%. The results indicated significant differences in the six treatments’ organic matter content (p < 0.05). When the P. aibuhitensis larvae initially attached to the sediment, the larvae’s density showed no significant difference among the six treatments. The density of larvae decreased gradually during the experimental period. It increased with the increasing organic matter content in sediment at every sampling time, but there was no significant difference (p > 0.05). The larvae’s specific growth rate in the first month was significantly higher than those in the second and third months (p < 0.05). The mortality showed no significance at different sediments in equal sampling times, but the mortality was lower in high organic matter content sediments. This study showed that the P. aibuhitensis larvae did not make an active selection; random selection happened when initially attached to the sediment with different organic matter contents. Higher organic matter content in the sediment was more conducive to larvae survival, and the organic matter content is the limitation factor on the mortality and the density. The different densities in the natural habitat of P. aibuhitensis might occur due to the passive selection by the environment

Delving into the Impacts of Different Easily Degradable Carbon Sources on the Degradation Characteristics of 2,4,6-Trichlorophenol and Microbial Community Properties

In chlorophenol wastewater treatment, adding easily degradable carbon sources, such as methanol, ethanol, sodium acetate, and sodium propionate, significantly improves the chlorophenol removal efficiency. This study systematically compares these conventional carbon sources in different sequencing batch reactors to understand their specific effects on both 2,4,6-trichlorophenol (2,4,6-TCP) degradation efficiency and microbial abundance. In a 35-day experiment, as a carbon source, ethanol exhibited a lower 2,4,6-TCP degradation concentration (77.56 mg/L) than those of methanol, sodium acetate, and sodium propionate, which achieved higher degradation concentrations: 123.89 mg/L, 170.96 mg/L, and 151.79 mg/L, respectively. As a carbon source, sodium acetate enhanced extracellular polymeric substance production (200.80 mg/g·VSS) by microorganisms, providing protection against the toxicity of chlorophenol and resulting in a higher 2,4,6-TCP removal concentration. Metagenomics identified crucial metabolic genes, including PcpA, chqB, Mal-r, pcaI, pcaF, and fadA. The abundance of genera containing the chqB gene correlated positively with the metabolic capacity for 2,4,6-TCP. Moreover, small molecular carbon sources such as methanol, sodium acetate, and sodium propionate promoted the enrichment of genera with functional genes

Study on Biodegradation Characteristics of Industrial Phenol-Containing Wastewater by Biological Co-Metabolism Technology

Biological co-metabolism is an economical and efficient technique for treating refractory organic matter, and in recent years, it has been widely used in the treatment of chlorophenol-containing wastewater. It has been found that many conditions affect the bio co-metabolism efficiency, such as the carbon source type, carbon source content, microorganism types, and environmental factors. The carbon source concentration experiment showed that when the dosage ratio of sodium acetate to black aniline powder was 1:2, the degradation rate of black aniline powder was 82%, and the removal rate was 92.9%. When tetrachlorophenol increased from 210 mg/L to 2100 mg/L, the tetrachlorophenol was increased in the effluent, and the microorganism's activity was inhibited. Besides, the sedimentation performance of activated sludge was also damaged. The temperature test showed that the removed 4-chlorophenol was as high as 2100 mg/L at 35 °C, and the apparent 4-chlorophenol residue in the effluent could be detected at 20 °C. Therefore, by appropriately controlling the external operating conditions of the reactor, the co-metabolism of refractory organic such as chlorophenols can be achieved

Research of advanced treatment technologies for chlorophenol wastewater

Chlorophenol wastewater belongs to highly toxic industrial wastewater, which can cause serious harm to the environment and human health if not treated effectively. The current treatment methods for chlorophenol wastewater are divided into physical, chemical, and biological methods. The physical adsorption experiment found that the monodisperse magnetic nano-column was prepared by the solvothermal method, which could remove 91.5% of pentachlorophenol within 30 mins. More than 90% of chlorophenol can be extracted using an ionic liquid as an extractant. When the chlorophenol reaches 15 g/L, the extraction rate only slightly decreases. CaO and SiO2 can achieve 99.0% 2,4,6-trichlorophenol in 6 hours as ball milling materials by physical and chemical methods. The electrochemical reduction test found that using Pd/Py SDBS/Ti as the cathode, 2-chlorophenol, 4-chlorophenol, and 3-chlorophenol could be reduced and dechlorinated, in which 100 mg/L of 2-chlorophenol could be completely degraded within 60 minutes. The biochemical index BOD5/COD of wastewater is less than 0.3 if the biological treatment technology based on co-metabolism is adopted to realize the chlorophenol treatment. In treating chlorophenol wastewater, the application scenario should be fully considered to achieve the best treatment effect of chlorophenol wastewater

Cloning and characterization of histone H3 and replacement histone H3.3 encoding genes of Manila clam (Ruditapes philippinarum)

456-464A full-length cDNA (rp-h3.3) encoding a replacement histone H3.3 had been identified in Manila clam (Ruditapes philippinarum). The cDNA consisted of 975 bp, including a ORF 411 bp in length, a 3′ untranslated regions 490 bp in length, a poly (A) tail and two polyadenylation signals. In addition, the cDNA encoded a peptide with the S.//.A.IG amino acid motif, which was identical to the replacement histone H3.3 variant. rpg-h3.3 and rp-h3s two sequences were obtained by amplifying the genomic DNA of R. philippinarum. The rpg-h3.3, which was the genomic DNA sequence of rp-h3.3, had one intron and the rp-h3s had no intron. It was predicted that h3s might be the h3l-like gene of R. philippinarum. Histone h3 (rp-h3) was also cloned from R. philippinarum genomic DNA. Therefore, the evolutionary origin between histone h3 and its replacement subtypes was analyzed. The study inclined to the viewpoint that h3l-like was the ancesteral gene of h3 and h3.3, which might be two different offsets from h3l-like. During histone evolution process, one copy of h3l-like genes became h3.3 by introns insertion and S-phase-coupled regulatory mechanisms lose, another copy became h3 by gene-duplication and accumulation of mutations in the S.//.A.IG motif

Phenological Shifts of the Deciduous Forests and Their Responses to Climate Variations in North America

Forests play a vital role in sequestering carbon dioxide from the atmosphere. Vegetation phenology is sensitive to climate changes and natural environments. Exploring the patterns in phenological events of the forests can provide useful insights for understanding the dynamics of vegetation growth and their responses to climate variations. Deciduous forest in North America is an important part of global forests. Here we apply time-series remote sensing imagery to map the critical dates of vegetation phenological events, including the start of season (SOS), end of season (EOS), and growth length (GL) of the deciduous forests in North America during the past two decades. The findings show that the SOS and EOS present considerable spatial and temporal variations. Earlier SOS, delayed EOS, and therefore extended GL are detected in a large part of the study area from temporal trend analysis over the years, though the magnitude of the trend varies at different locations. The phenological events are found to correlate to the environmental factors and the impact on the vegetation phenology from the factors is location-dependent. The findings confirm that the phenology of the deciduous forests in North America is updated such as advanced SOS and delayed EOS in the last two decades and the climate variations are likely among the driving forces for the updates. Considering that previous studies warn that shifts in vegetation phenology could reverse the role of forests as net emitters or net sinks, we suggest that forest management should be strengthened to forests that experience significant changes in the phenological events