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Is part of the Bibliography
- no (258)
Energy-efficient components do not automatically lead to energy-efficient systems. Technical Operations Research (TOR) shifts the focus from the single component to the system as a whole and finds its optimal topology and operating strategy simultaneously. In previous works, we provided a preselected construction kit of suitable components for the algorithm. This approach may give rise to a combinatorial explosion if the preselection cannot be cut down to a reasonable number by human intuition. To reduce the number of discrete decisions, we integrate laws derived from similarity theory into the optimization model. Since the physical characteristics of a production series are similar, it can be described by affinity and scaling laws. Making use of these laws, our construction kit can be modeled more efficiently: Instead of a preselection of components, it now encompasses whole model ranges. This allows us to significantly increase the number of possible set-ups in our model. In this paper, we present how to embed this new formulation into a mixed-integer program and assess the run time via benchmarks. We present our approach on the example of a ventilation system design problem.
Gearboxes are mechanical transmission systems that provide speed and torque conversions from a rotating power source. Being a central element of the drive train, they are relevant for the efficiency and durability of motor vehicles. In this work, we present a new approach for gearbox design: Modeling the design problem as a mixed-integer nonlinear program (MINLP) allows us to create gearbox designs from scratch for arbitrary requirements and—given enough time—to compute provably globally optimal designs for a given objective. We show how different degrees of freedom influence the runtime and present an exemplary solution.
A high-Q resonance-mode measurement of EIS capacitive sensor by elimination of series resistance
(2017)
An EIS capacitive sensor is a semiconductor-based potentiometric sensor, which is sensitive to the ion concentration or pH value of the solution in contact with the sensing surface. To detect a small change in the ion concentration or pH, a small capacitance change must be detected. Recently, a resonance-mode measurement was proposed, in which an inductor was connected to the EIS capacitive sensor and the resonant frequency was correlated with the pH value. In this study, the Q factor of the resonant circuit was enhanced by canceling the internal resistance of the reference electrode and the internal resistance of the inductor coil with the help of a bypass capacitor and a negative impedance converter, respectively. 1% variation of the signal in the developed system corresponded to a pH change of 3.93 mpH, which was about 1/12 of the conventional method, suggesting a better performance in detection of a small pH change.
The gene encoding a putative (R,R)-butane-2,3-diol dehydrogenase (bdhA) from Bacillus clausii DSM 8716T was isolated, sequenced and expressed in Escherichia coli. The amino acid sequence of the encoded protein is only distantly related to previously studied enzymes (identity 33–43%) and exhibited some uncharted peculiarities. An N-terminally StrepII-tagged enzyme variant was purified and initially characterized. The isolated enzyme catalyzed the (R)-specific oxidation of (R,R)- and meso-butane-2,3-diol to (R)- and (S)-acetoin with specific activities of 12 U/mg and 23 U/mg, respectively. Likewise, racemic acetoin was reduced with a specific activity of up to 115 U/mg yielding a mixture of (R,R)- and meso-butane-2,3-diol, while the enzyme reduced butane-2,3-dione (Vmax 74 U/mg) solely to (R,R)-butane-2,3-diol via (R)-acetoin. For these reactions only activity with the co-substrates NADH/NAD+ was observed. The enzyme accepted a selection of vicinal diketones, α-hydroxy ketones and vicinal diols as alternative substrates. Although the physiological function of the enzyme in B. clausii remains elusive, the data presented herein clearly demonstrates that the encoded enzyme is a genuine (R,R)-butane-2,3-diol dehydrogenase with potential for applications in biocatalysis and sensor development.