Transient Simulation of Small-Capacity Reciprocating Compressors for On-Off Controlled Refrigerators

This paper presents a simulation model for the transient behavior of vapor compression refrigerating appliances subjected to on-off control patterns focusing on the reciprocating compressor. A detailed compressor model is put forward based on two sub-models: one for the compression cycle, which can predict the valve dynamics, heat transfer in the compression chamber and the pressure pulsations in mufflers, and the other for the compressor shell, which calculates the temperature and mass flow rate in components other than the compression chamber. The remaining components of the single-door frost-free refrigerator considered in this work (i.e. condenser, evaporator, refrigerated compartment) are modeled based on mass and energy balances considering each component as an even lump. The expansion device and the refrigerant charge sub-models are replaced by prescribed condenser subcooling and evaporator superheating degrees, respectively. The overall cycle simulation model was validated by comparing predictions for the compressor temperatures and mass flow rate, indicated power, power consumption and overall energy consumption with the experimental counterparts measured in a household refrigerator, whose components – including the compressor – were carefully instrumented with thermocouples and pressure transducers, and tested in a climate chamber with a strict control of air temperature, humidity and velocity. Finally, sensitivity analyses were conducted to compare the effect of the compressor design parameters on its performance under calorimeter and actual system conditions

Triple seesaw mechanism

On fitting the type II seesaw mechanism into the type I seesaw mechanism, we obtain a formula to the neutrino masses which get suppressed by high-scale $M^3$ in its denominator. As a result, light neutrinos are naturally obtained with new physics at TeV scale. As interesting consequence, the mechanism may be directly probed at the LHC by directly producing the TeV states intrinsic of the mechanism. We show that the 3-3-1 model with right-handed neutrinos realizes naturally such seesaw mechanism.Comment: About 13 pages, no figure

Navigation Constellation Design Using a Multi-Objective Genetic Algorithm

In satellite constellation design, performance and cost of the system drive the design process. The Global Positioning System (GPS) constellation is currently used to provide positioning and timing worldwide. As satellite technology has improved over the years, the cost to develop and maintain the satellites has increased. Using a constellation design tool, it is possible to analyze the tradeoffs of new navigation constellation designs (Pareto fronts) that illustrate the tradeoffs between position dilution of precision (PDOP) and system cost. This thesis utilized Satellite Tool Kit (STK) to calculate PDOP values of navigation constellations, and the Unmanned Spacecraft Cost Model (USCM) along with the Small Spacecraft Cost Model (SSCM) to determine system cost. The design parameters used include Walker constellation parameters, orbital elements, and transmit power. The results show that the constellation design tool produces realistic solutions. Using the generated solutions, an analysis of the navigation constellation designs was presented

Bistability, softening, and quenching of magnetic moments in Ni-filled carbon nanotubes

The authors apply first-principles calculations to investigate the interplay between structural, electronic, and magnetic properties of nanostructures composed of narrow nanotubes filled with metallic nanowires. The focus is on the structural and magnetic responses of Ni-filled nanotubes upon radial compression. Interestingly, metastable flattened structures are identified, in which radially deformed nanotubes are stabilized by the interactions with the encapsulated wire. Moreover, our results indicate a quenching of the magnetic moment of the wire upon compression, as a result of the transfer of charge from the $s$ to the $d$ orbitals of the atoms in the wire.Comment: 4 pages, 4 figure

Sequential Allocation and Balancing Prognostic Factors in a Psychiatric Clinical Trial

In controlled clinical trials, each of several prognostic factors should be balanced across the trial arms. Traditional restricted randomization may be proved inadequate especially with small sample sizes. In psychiatric disorders such as obsessive compulsive disorder (OCD), small trials prevail. Therefore, procedures to minimize the chance of imbalance between treatment arms are advisable. This paper describes a minimization procedure specifically designed for a clinical trial that evaluates treatment efficacy for OCD patients. Aitchison's compositional distance was used to calculate vectors for each possibility of allocation in a covariate adaptive method. Two different procedures were designed to allocate patients in small blocks or sequentially one-by-one. Partial results of this allocation procedure as well as simulated ones are shown. In the clinical trial for which this procedure was developed, the balancing between treatment arms was achieved successfully. Simulations of results considering different arrival order of patients showed that most of the patients are allocated in a different treatment arm if arrival order is modified. Results show that a random factor is maintained with the random arrival order of patients. This specific procedure allows the use of a large number of prognostic factors for the allocation decision and was proved adequate for a psychiatric trial design

Aesthetics after the Ontological Turn: An Ecological Approach to Artificial Creativity

The development of chatbots and other generative systems powered by AI, particularly the latest version of ChatGPT, rekindled many discussions on topics such as intelligence and creativity, even leading some to suggest that we may be undergoing a “fourth narcissistic wound”. Starting from Margaret Boden’s approach to creativity, we will argue that if computational systems have always excelled at combinatorial creativity, current AI systems stand out at exploratory creativity but are perceived as still falling flat regarding transformational creativity. This paper explores some of the reasons for this, including how, despite the immensity of the conceptual space that results from training of large language models and other machine learning systems, these systems do not, for the most part, share models of the world with us, thus becoming cognitively inaccessible. This paper argues that rather than trying to bring AI systems to imitate us, our umwelt and psychology, to understand their full creative potential, we need to understand them from an ecological and non-anthropocentric perspective that implies an ontological turn both in science and technology studies and in art studies