Direct matching between the flow factor approach model and molecular dynamics simulation for nanochannel flows

Mathematically formulating nanochannel flows is challenging. Here, the values of the characteristic parameters were extracted from molecular dynamics simulation (MDS), and directly input to the closed-form explicit flow factor approach model (FFAM) for nanochannel flows. By this way, the physical nature of the simulated system in FFAM is the same with that in MDS. Two nano slit channel heights respectively with two different liquid-channel wall interactions were addressed. The flow velocity profiles across the channel height respectively calculated from MDS and FFAM were compared. By introducing the equivalent value $${{\Delta_{im} } \mathord{\left/ {\vphantom {{\Delta_{im} } D}} \right. \kern-\nulldelimiterspace} D}$$ Δ im / D , FFAM fairly agrees with MDS for all the cases. The study values FFAM in simulating nanochannel flows.

Techno-Economic Analysis on an Industrial-Scale Production System of Polyhydroxyalkanoates (PHA) from Cheese By-Products by Halophiles

Polyhydroxyalkanoates (PHA) are a family of biodegradable plastics used as an ecofriendly alternative for conventional plastics in various applications. In this study, an industrial-scale PHA production system was designed and analyzed for the material flows and economics with the use of SuperPro Designer. Haloferax mediterranei was utilized to produce poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV). Byproduct streams from a local cheese plant, with an input of 168.7 metric ton/day (MT/day) lactose, were used as the feedstock. Three scenarios with different processes for the treatments of used enzyme and spent medium were investigated and the major factors that influence the overall economics were identified. The simulated system produces 9700 MT/year PHBV with a yield of 0.2 g PHBV/g lactose and an overall process efficiency of 87%. The breakeven price was found to be more sensitive to the lactose price than enzyme price. The scenario with enzyme reuse and spent medium recycling achieved the lowest breakeven price among others, which can be less than 4 $/kg PHA based on the delactosed permeate (DLP) unit price. The study suggests utilizing dairy derived feedstocks has the potential to make PHA competitive in the bioplastic market, which could be beneficial to both dairy and bioplastic industries.

Play for Real(ism) - Using Games to Predict Human-AI interactions in the Real World

AI-enabled decision support systems have repeatedly failed in real world applications despite the underlying model operating as designed. Often this was because the system was used in an unexpected manner. Our goal is to enable better prediction of how systems will be used prior to their implementation as well as to improve existing designs, by taking human behavior into account. There are several challenges to collecting such data. Not having access to an existing prediction engine requires the simulation of such a system's behavior. This simulation must include not just the behavior of the underlying model but also the context in which the decision will be made in the real world. Additionally, collecting statistically valid samples requires that test subjects make repeated choices under slightly varied conditions. Unfortunately, in such repetitious conditions fatigue can quickly set in. Games provide us the ability to address both of these challenges by providing both systems context and narrative context. Systems context can be used to convey some or all of the information the player needs to make a decision in the game environment itself, which can help avoid the onset of fatigue. Narrative context can provide a broader environment within which the simulated system operates, adding a sense of progress, showing the effect of decisions, adding perceived social norms, and setting incentives and stakes. This broader environment can further prevent player fatigue while replicating many of the external factors that might affect choices in the real world. In this paper we describe the design of the Human-AI Decision Evaluation System (HADES), a test harness capable of interfacing with a game environment, simulating the behavior of an AI-enabled decision support system, and collecting the results of human decision making based upon such a system's predictions. Additionally, we present an analysis of data collected by HADES while interfaced with a visual novel game focused on software cyber-risk assessment.

Effect of the THF molecules on the hydrate cavities formation with adding NaCL molecules into the modeling system

In this work, using molecular dynamics methods by Gromacs package we simulate the hydrate formation in systems containing THF, water, and NACL molecules at different thermodynamic conditions and concentration of THF molecules. The curves of the number of hydrogen bonds are obtained depending on the simulation time at different temperatures. The computer simulations results show that the hydrogen bonds between THF and water molecules are relatively weak, with a maximum number of two water molecules hydrogen bonded to THF, but THF can facilitate water molecules rearrangement to form a pentagonal or hexagonal planar ring that is the part of clathrate cavity. In addition, the THF molecule can significantly increase the likelihood to form clathrate cavities suitable for the second guest molecule. The effect of THF molecules concentration on the hydrate cavities formation with adding NaCL molecules into the modeling system is shown. In this work, data are obtained on the magnitude of torsion angles, the percentage of which increases depending on the simulation time, which allows concluding that labile large and small cavities of sII hydrates are formed. The increase in the THF molecules concentration is shown to lead to a decrease in the hydrogen bonds number of water molecules in the simulated system.

Machine Learning MOSA Monitoring System

This research paper deals with the problem of Metal-Oxide Surge Arrester (MOSA) condition monitoring and a new methodology in surge arrester monitoring and diagnostics is presented. A machine learning algorithm (back propagation regression) is used to estimate the non-linearity coefficient of the surge arrester, based on operating voltage and leakage current of the arrester. Using a simulated system, this research investigates the possibility of application and efficiency of machine learning. It is shown that the applied learning algorithm results are competitive with the model results parameters calculated as R2 = 0.999 and mean absolute real error computed as 0.005 which has shown that the proposed model can be used for MOSA monitoring and diagnostic purposes.

Overlimiting current near a nanochannel a new insight using molecular dynamics simulations

In this paper, we report for the first time overlimiting current near a nanochannel using all-atom molecular dynamics (MD) simulations. Here, the simulated system consists of a silicon nitride nanochannel integrated with two reservoirs. The reservoirs are filled with $${0.1} \, \hbox {M}$$ 0.1 M potassium chloride (KCl) solution. A total of $${\sim } 1.1$$ ∼ 1.1 million atoms are simulated with a total simulation time of $${\sim } 1 {\mu s}$$ ∼ 1 μ s over $${\sim }$$ ∼ 30000 CPU hours using 128 core processors (Intel(R) E5-2670 2.6 GHz Processor). The origin of overlimiting current is found to be due to an increase in chloride ($${Cl^-}$$ C l - ) ion concentration inside the nanochannel leading to an increase in ionic conductivity. Such effects are seen due to charge redistribution and focusing of the electric field near the interface of the nanochannel and source reservoir. Also, from the MD simulations, we observe that the earlier theoretical and experimental postulations of strong convective vortices resulting in overlimiting current are not the true origin for overlimiting current. Our study may open up new theories for the mechanism of overlimiting current near the nanochannel interconnect devices.

BUSINESS ASSESSMENT OF "SMART CITY" COMMUNICATION INFRASTRUCTURE

Любая модель должна быть адекватной и конструктивной, т.е. обеспечивать эффективное и целенаправленное использование, в том числе для анализа критичности к изменению параметров моделируемой системы. Применяемые во многих компаниях при маркетинговых расчетах громоздкие и негибкие финансовые Excel-построения не позволяют инвестору оперативно принимать решения об экономической целесообразности проекта. Предлагается алгоритм, упрощающий эту задачу применительно к облачным радиомодулям RAN. Any model must be adequate and constructive, i.e. ensure its efficient and purposeful use, including for the analysis of criticality to changes in the parameters of the simulated system. The cumbersome and inflexible financial Excel constructions used in many companies in marketing calculations do not allow the investor to make quickly decisions about the economic feasibility of the project. An algorithm that simplifies this task in relation to cloud RAN radio modules is proposed.

Simulation Data Acquisition and Control for LNG Custody Transfer Based on ISO 8943

Liquefied Natural Gas (LNG) is a complex mixture of low-molecular-weight hydrocarbons with nitrogen as a principal inert impurity. Nowadays, the instrumentation control tools are needed in LNG Commercialization to ensure the LNG is safely transported, while minimizing the energy losses across the network. This research was a preliminary design that used LNG custody transfer control tools referred the ISO 8943:2007 standard. The temperature was measured by thermocouple (Rosemount transmitter 3144 series), while the pressure was measured using pressure transmitter (Rosemount transmitter 3051 series). The simulated signal temperature was done by temperature control box, while the simulated pressure was represented by WIKA pressure calibrator. Data from transmitter was sent to the LabVolt 9063 series that has data acquisition for Software Development Kit (SDK) enabled. Previously, the LabVolt 9063 did not recognized the signal from the transmitter. The SDK software bridged the LabVolt hardware with the LabView software. In the simulated system, temperature alarm will be triggered when the temperature value exceeds 20oC. For simulated pressure, the alarm will respond if pressure value exceeds 30 psi. From the results of this research, the communication between hardware and software worked properly. The data acquisition system was stable during the data collection stage, processing and displaying. In addition, the alarm indicator for both temperature and pressure was met within the threshold value.