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The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition.
In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon.
To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed.
Cross sections for neutron-induced reactions of short-lived nuclei are essential for nuclear astrophysics since these reactions in the stars are responsible for the production of most heavy elements in the universe. These reactions are also key in applied domains like energy production and medicine. Nevertheless, neutron-induced cross-section measurements can be extremely challenging or even impossible to perform due to the radioactivity of the targets involved. Indirect measurements through the surrogate-reaction method can help to overcome these difficulties.
The surrogate-reaction method relies on the use of an alternative reaction that will lead to the formation of the same excited nucleus as in the neutron-induced reaction of interest. The decay probabilities (for fission, neutron and gamma-ray emission) of the nucleus produced via the surrogate reaction allow one to constrain models and the prediction of the desired neutron cross sections.
We propose to perform surrogate reaction measurements in inverse kinematics at heavy-ion storage rings, in particular at the CRYRING@ESR of the GSI/FAIR facility. We present the conceptual idea of the most promising setup to measure for the first time simultaneously the fission, neutron and gamma-ray emission probabilities. The results of the first simulations considering the 238U(d,d') reaction are shown, as well as new technical developments that are being carried out towards this set-up.
Stored and cooled, highly-charged ions offer unprecedented capabilities for precision studies in the realm of atomic, nuclear structure and astrophysics[1]. After the successful investigation of the 96Ru(p,7)97Rh reaction cross section in 2009[2], the first measurement of the 124Xe(p,7)125Cs reaction cross section has been performed with decelerated, fully-ionized 124Xe ions in 2016 at the Experimental Storage Ring (ESR) of GSI[3]. Using a Double Sided Silicon Strip Detector, introduced directly into the ultra-high vacuum environment of a storage ring, the 125Cs proton-capture products have been successfully detected. The cross section has been measured at 5 different energies between 5.5AMeV and 8AMeV, on the high energy tail of the Gamow-window for hot, explosive scenarios such as supernovae and X-ray binaries. The elastic scattering on the H2 gas jet target is the major source of background to count the (p,7) events. Monte Carlo simulations show that an additional slit system in the ESR in combination with the energy information of the Si detector will enable background free measurements of the proton-capture products. The corresponding hardware is being prepared and will increase the sensitivity of the method tremendously.
Muscular activity in terms of surface electromyography (sEMG) is usually normalised to maximal voluntary isometric contractions (MVICs). This study aims to compare two different MVIC-modes in handcycling and examine the effect of moving average window-size. Twelve able-bodied male competitive triathletes performed ten MVICs against manual resistance and four sport-specific trials against fixed cranks. sEMG of ten muscles [M. trapezius (TD); M. pectoralis major (PM); M. deltoideus, Pars clavicularis (DA); M. deltoideus, Pars spinalis (DP); M. biceps brachii (BB); M. triceps brachii (TB); forearm flexors (FC); forearm extensors (EC); M. latissimus dorsi (LD) and M. rectus abdominis (RA)] was recorded and filtered using moving average window-sizes of 150, 200, 250 and 300 ms. Sport-specific MVICs were higher compared to manual resistance for TB, DA, DP and LD, whereas FC, TD, BB and RA demonstrated lower values. PM and EC demonstrated no significant difference between MVIC-modes. Moving average window-size had no effect on MVIC outcomes. MVIC-mode should be taken into account when normalised sEMG data are illustrated in handcycling. Sport-specific MVICs seem to be suitable for some muscles (TB, DA, DP and LD), but should be augmented by MVICs against manual/mechanical resistance for FC, TD, BB and RA.
The manufacturing share of laser powder bed fusion (L-PBF) increases in industrial application, but still many process steps are manually operated. Additionally, it is not possible to achieve tight dimensional tolerances or low surfaces roughness. Hence, a process chain has to be set up to combine additive manufacturing (AM) with further machining technologies. To achieve a continuous workpiece flow as basis for further industrialization of L-PBF, the paper presents a novel substrate system and its application on L-PBF machines and post-processing. The substrate system consists of a zero-point clamping system and a matrix-like interface of contact pins to be substantially connected to the workpiece within the L-PBF process.
In this study, we describe the manufacturing and characterization of silk fibroin membranes derived from the silkworm Bombyx mori. To date, the dissolution process used in this study has only been researched to a limited extent, although it entails various potential advantages, such as reduced expenses and the absence of toxic chemicals in comparison to other conventional techniques. Therefore, the aim of this study was to determine the influence of different fibroin concentrations on the process output and resulting membrane properties. Casted membranes were thus characterized with regard to their mechanical, structural and optical assets via tensile testing, SEM, light microscopy and spectrophotometry. Cytotoxicity was evaluated using BrdU, XTT, and LDH assays, followed by live–dead staining. The formic acid (FA) dissolution method was proven to be suitable for the manufacturing of transparent and mechanically stable membranes. The fibroin concentration affects both thickness and transparency of the membranes. The membranes did not exhibit any signs of cytotoxicity. When compared to other current scientific and technical benchmarks, the manufactured membranes displayed promising potential for various biomedical applications. Further research is nevertheless necessary to improve reproducible manufacturing, including a more uniform thickness, less impurity and physiological pH within the membranes.
Additive manufacturing (AM) works by creating objects layer by layer in a manner similar to a 2D printer with the “printed” layers stacked on top of each other. The layer-wise manufacturing nature of AM enables fabrication of freeform geometries which cannot be fabricated using conventional manufacturing methods as a one part. Depending on how each layer is created and bonded to the adjacent layers, different AM methods have been developed. In this chapter, the basic terms, common materials, and different methods of AM are described, and their potential applications are discussed.
Safety of subjects during radiofrequency exposure in ultra-high-field magnetic resonance imaging
(2020)
Magnetic resonance imaging (MRI) is one of the most important medical imaging techniques. Since the introduction of MRI in the mid-1980s, there has been a continuous trend toward higher static magnetic fields to obtain i.a. a higher signal-to-noise ratio. The step toward ultra-high-field (UHF) MRI at 7 Tesla and higher, however, creates several challenges regarding the homogeneity of the spin excitation RF transmit field and the RF exposure of the subject. In UHF MRI systems, the wavelength of the RF field is in the range of the diameter of the human body, which can result in inhomogeneous spin excitation and local SAR hotspots. To optimize the homogeneity in a region of interest, UHF MRI systems use parallel transmit systems with multiple transmit antennas and time-dependent modulation of the RF signal in the individual transmit channels. Furthermore, SAR increases with increasing field strength, while the SAR limits remain unchanged. Two different approaches to generate the RF transmit field in UHF systems using antenna arrays close and remote to the body are investigated in this letter. Achievable imaging performance is evaluated compared to typical clinical RF transmit systems at lower field strength. The evaluation has been performed under consideration of RF exposure based on local SAR and tissue temperature. Furthermore, results for thermal dose as an alternative RF exposure metric are presented.
Multi-enzyme immobilization onto a capacitive field-effect biosensor by nano-spotting technique is presented. The nano-spotting technique allows to immobilize different enzymes simultaneously on the sensor surface with high spatial resolution without additional photolithographical patterning. The amount of applied enzymatic cocktail on the sensor surface can be tailored. Capacitive electrolyte-insulator-semiconductor (EIS) field-effect sensors with Ta2O5 as pH-sensitive transducer layer have been chosen to immobilize the three different (pL droplets) enzymes penicillinase, urease, and glucose oxidase. Nano-spotting immobilization is compared to conventional drop-coating method by defining different geometrical layouts on the sensor surface (fully, half-, and quarter-spotted). The drop diameter is varying between 84 µm and 102 µm, depending on the number of applied drops (1 to 4) per spot. For multi-analyte detection, penicillinase and urease are simultaneously nano-spotted on the EIS sensor. Sensor characterization was performed by C/V (capacitance/voltage) and ConCap (constant capacitance) measurements. Average penicillin, glucose, and urea sensitivities for the spotted enzymes were 81.7 mV/dec, 40.5 mV/dec, and 68.9 mV/dec, respectively.