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With the increased interest for interstellar exploration after the discovery of exoplanets and the proposal by Breakthrough Starshot, this paper investigates the optimisation of photon-sail trajectories in Alpha Centauri. The prime objective is to find the optimal steering strategy for a photonic sail to get captured around one of the stars after a minimum-time transfer from Earth. By extending the idea of the Breakthrough Starshot project with a deceleration phase upon arrival, the mission’s scientific yield will be increased. As a secondary objective, transfer trajectories between the stars and orbit-raising manoeuvres to explore the habitable zones of the stars are investigated. All trajectories are optimised for minimum time of flight using the trajectory optimisation software InTrance. Depending on the sail technology, interstellar travel times of 77.6-18,790 years can be achieved, which presents an average improvement of 30% with respect to previous work. Still, significant technological development is required to reach and be captured in the Alpha-Centauri system in less than a century. Therefore, a fly-through mission arguably remains the only option for a first exploratory mission to Alpha Centauri, but the enticing results obtained in this work provide perspective for future long-residence missions to our closest neighbouring star system.
The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs.
The immobilization of NAD+-dependent dehydrogenases, in combination with a diaphorase, enables the facile development of multiparametric sensing devices. In this work, an amperometric biosensor array for simultaneous determination of ethanol, formate, d- and l-lactate is presented. Enzyme immobilization on platinum thin-film electrodes was realized by chemical cross-linking with glutaraldehyde. The optimization of the sensor performance was investigated with regard to enzyme loading, glutaraldehyde concentration, pH, cofactor concentration and temperature. Under optimal working conditions (potassium phosphate buffer with pH 7.5, 2.5 mmol L-1 NAD+, 2.0 mmol L-1 ferricyanide, 25 °C and 0.4% glutaraldehyde) the linear working range and sensitivity of the four sensor elements was improved. Simultaneous and cross-talk free measurements of four different metabolic parameters were performed successfully. The reliable analytical performance of the biosensor array was demonstrated by application in a clarified sample of inoculum sludge. Thereby, a promising approach for on-site monitoring of fermentation processes is provided.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based potentiometric device, which detects concentration changes of an analyte solution on the sensor surface in a spatially resolved way. It uses a light source to generate electron–hole pairs inside the semiconductor, which are separated in the depletion region due to an applied bias voltage across the sensor structure and hence, a surface-potential-dependent photocurrent can be read out. However, depending on the beam angle of the light source, scattering effects can occur, which influence the recorded signal in LAPS-based differential measurements. To solve this problem, a novel illumination unit based on a field programmable gate array (FPGA) consisting of 16 small-sized tunable infrared laser-diode modules (LDMs) is developed. Due to the improved focus of the LDMs with a beam angle of only 2 mrad, undesirable scattering effects are minimized. Escherichia coli (E. coli) K12 bacteria are used as a test microorganism to study the extracellular acidification on the sensor surface. Furthermore, a salt bridge chamber is built up and integrated with the LAPS system enabling multi-chamber differential measurements with a single Ag/AgCl reference electrode.
High gradient magnetic separation (HGMS) has been established since the early 1970s. A more recent application of these systems is the use in bioprocesses. To integrate the HGMS in a fermentation process, it is necessary to optimize the separation matrix with regard to the magnetic separation characteristics and permeability of the non-magnetizable components of the fermentation broth. As part of the work presented here, a combined fluidic and magnetic force finite element model simulation was created using the software COMSOL Multiphysics and compared with separation experiments. Finally, as optimal lattice orientation of the separation matrix, a transversal rhombohedral arrangement was defined. The high suitability of the new filter matrix has been verified by separation experiments.
Optimization of Interplanetary Rendezvous Trajectories for Solar Sailcraft Using a Neurocontroller
(2002)
Generally, the quality of a weld joint is directly influenced by the welding input parameter settings. Selection of proper process parameters is important to obtain the desired weld bead profile and quality. In this research work, numerical and graphical optimization techniques of the CO2 laser beam welding of dual phase (DP600)/transformation induced plasticity (TRIP700) steel sheets were carried out using response surface methodology (RSM) based on Box–Behnken design. The procedure was established to improve the weld quality, increase the productivity and minimize the total operation cost by considering the welding parameters range of laser power (2–2.2 kW), welding speed (40–50 mm/s) and focus position (−1 to 0 mm). It was found that, RSM can be considered as a powerful tool in experimental welding optimization, even when the experimenter does not have a model for the process. Strong, efficient and low cost weld joints could be achieved using the optimum welding conditions.
Optimization of passivation layers for corrosion protection of silicon-based microelectrode arrays
(2000)
Bacillus subtilis and Bacillus licheniformis are widely used for the large-scale industrial production of proteins. These strains can efficiently secrete proteins into the culture medium using the general secretion (Sec) pathway. A characteristic feature of all secreted proteins is their N-terminal signal peptides, which are recognized by the secretion machinery. Here, we have studied the production of an industrially important secreted protease, namely, subtilisin BPN′ from Bacillus amyloliquefaciens. One hundred seventy-three signal peptides originating from B. subtilis and 220 signal peptides from the B. licheniformis type strain were fused to this secretion target and expressed in B. subtilis, and the resulting library was analyzed by high-throughput screening for extracellular proteolytic activity. We have identified a number of signal peptides originating from both organisms which produced significantly increased yield of the secreted protease. Interestingly, we observed that levels of extracellular protease were improved not only in B. subtilis, which was used as the screening host, but also in two different B. licheniformis strains. To date, it is impossible to predict which signal peptide will result in better secretion and thus an improved yield of a given extracellular target protein. Our data show that screening a library consisting of homologous and heterologous signal peptides fused to a target protein can identify more-effective signal peptides, resulting in improved protein export not only in the original screening host but also in different production strains.
Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.