Charge-based superconducting digital logic family using quantum phase-slip junctions

Superconducting digital computing systems, primarily involving Josephson junctions are actively being pursued as high performance and low energy dissipating alternatives to CMOS-based technologies for petascale and exascale computers, although several challenges still exist in overcoming barriers to practically implement these technologies. In this paper, we present an alternative superconducting logic structure: quantized charge-based logic circuits using quantum phase-slip junctions, which have been identified as dual devices to Josephson junctions. Basic principles of logic implementation using quantum phase-slips are presented in simulations with the help of a SPICE model that has been developed for the quantum phase-slip structures. Circuit elements that form the building blocks for complex logic circuit design are introduced. Two different logic gate designs: OR gate and XOR gate are presented to demonstrate the usage of the building blocks introduced.Comment: 4 pages, 8 figures, EuCAS 201

Throughput Optimization in High Speed Downlink Packet Access (HSDPA)

In this paper, we investigate throughput optimization in High Speed Downlink Packet Access (HSDPA). Specifically, we propose offline and online algorithms for adjusting the Channel Quality Indicator (CQI) used by the network to schedule data transmission. In the offline algorithm, a given target BLER is achieved by adjusting CQI based on ACK/NAK history. By sweeping through different target BLERs, we can find the throughput optimal BLER offline. This algorithm could be used not only to optimize throughput but also to enable fair resource allocation among mobile users in HSDPA. In the online algorithm, the CQI offset is adapted using an estimated short term throughput gradient without specifying a target BLER. An adaptive stepsize mechanism is proposed to track temporal variation of the environment. We investigate convergence behavior of both algorithms. Simulation results show that the proposed offline algorithm can achieve the given target BLER with good accuracy. Both algorithms yield up to 30% HSDPA throughput improvement over that with 10% target BLER

A novel sponge-submerged membrane bioreactor (SSMBR) for wastewater treatment and reuse

Membrane fouling has been regarded as one of the biggest challenges to widespread application of membrane bioreactor (MBR). This study focuses on minimizing the membrane fouling and improving the performance of submerged membrane bioreactor (SMBR) by porous sponge addition. The effects of sponge addition on sustainable flux and membrane fouling were investigated. Acclimatized sponge could significantly increase the suspended growth in SMBR with biomass of 16.7g/L(sponge). With the sponge volume fraction of 10%, SSMBR could enhance sustainable flux up to 50L/m2h compared with sustainable flux of SMBR (only 25L/m2h). SSMBR also exhibited excellent results in terms of DOC removal (over 95%), COD removal (over 97%), lower transmembrane pressure development, and oxygen uptake rate. Over 89% of NH4-N and 98% of PO4-P were removed when SSMBR was operated with a MLSS concentration of 15g/L

How and When Do I Validate, Proof Test and Re-Validate My SIS logic Solver?

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Parametric modeling of bolted joints between components made of particulate composite materials

Particulate metal matrix composites (MMC) exhibit higher stiffness, strength and wear resistance compared to metal alloys. They exhibit superior compressive and buckling strength because of their higher plastic modulus. MMC\u27s can operate at very higher temperatures than fiber-reinforced polymer composites. Their isotropic behavior and forming ability by conventional methods makes them a better choice for low-cost applications. They have good thermal conductivity, high electrical conductivity and low thermal expansion.;The main objective of this study is to predict numerically the stress distributions around the hole in a bolted joint made of particulate metal matrix composite and to investigate the associated load transfer efficiencies both for a single and double lap bolted joints. A three dimensional Finite Element parametric model has been developed to study the effects of various design parameters on the structural performance of such joints.;Single lap bolted joints experience bending when tension load is applied to the joint because of the unsymmetrical configuration of the joint. This effect is reduced in double lap bolted joints due to their symmetry. This research quantifies the relationship between the stress around the hole in bolted joints and the washer diameter, bolt diameter, tightening pressure, and the clearance between the hole and the bolt. It has also been observed that variations in Young\u27s Modulus have no insignificant effect on the stress concentration around the hole

SPICE model implementation of a quantum phase-slip junction

A quantum phase-slip is a superconducting phenomenon, which is identified as an exact dual to Josephson tunneling. Therefore, the device known as a quantum phase-slip junction is expected to be as significant and fundamental as the Josephson junction in superconductors. Josephson junctions in general, have several applications in millimeter wave detection, the voltage standard, digital circuits and also qubits. The aim of this thesis is to demonstrate a SPICE model of a quantum phase-slip junction to aid the search for analogous classical applications in fields of digital and RF circuits. Derivation of a SPICE model of a quantum phase-slip junction using its known compact model, and implementation in JSPICE using C programming language along with implementation in WRSPICE using Verilog-A have been presented in this thesis. This model includes transient operation of the device. Basic I-V curves along with simulation of example circuits of the device are shown to validate the model

Adding renewables to the grid: Effects of Storage and Stochastic Forecasting

The electricity sector contributes to a quarter of global greenhouse emissions, and managing its evolution is a critical sustainability challenge. The context for the development and operation of electricity grids has dramatically changed in recent years. Wind and solar power have become much less expensive. Lower costs combined with increased policy action to address carbon emissions is leading to substantial shares of electricity generated by intermittent renewables. Maintaining a stable electricity supply with intermittency is a critical challenge; storage and natural gas are possible solutions. While policymakers promote storage as green grid technology, low-cost natural gas from hydrofracturing extraction raises the economic hurdle for storage. Researchers have developed complicated energy system models to help plan grids in the face of the above trends. The research in this dissertation introduces new modeling features that affect the economic and environmental outcomes of the adoption of renewable and storage technologies. First, prior models that explore the future build-out of electricity grids are nearly always deterministic, i.e., they assume that decision-makers have perfect information. Here a stochastic optimization grid expansion model is developed that presumes that expected future fluctuations, e.g. in fuel prices, influence build-out decisions. This stochastic model thus includes uncertainty and risk as core elements: Grid build-out depends on the distribution of system costs. A genetic algorithm with Monte-Carlo simulation is used for co-optimization using two objective functions: “risk-neutral,” which optimizes to minimize average system cost and “risk-averse,” which optimizes to minimize average of the top 5% of costs (also called 95% Conditional Value at Risk (CVaR)). This model is tested for the US Midwest regional grid. The results show that the risk-averse scenario does not increase mean system costs but adds significantly more wind. These results corroborate prior work showing that electricity system costs can be surprisingly inelastic to renewable adoption and further introduces quantification of how increased renewables lowers cost risk. Second, the economic and environmental performance of storage is complicated by how its introduction affects the operation of both renewable and fossil plants. In this dissertation, a model is developed that accounts for how storage operation would affect prices on the grid and in turn, the operational schedule that yields optimal revenue. Results from modeling the US Midwest region shows that this treatment of storage as a “price maker” affects results. The model indicates that storage increases carbon emissions when it enables a high emissions generator, such as a coal plant, to substitute for a cleaner plant, such as natural gas. In this case, low cost; efficient natural gas generation is relatively better than coal to realize emissions reductions with storage under economic arbitrage until renewables dominate the grid mix. Third, the operational strategies of energy storage alter the generation and profits of the other electricity generation systems. The operational effects of storage on the change in generation is investigated for all the eGRID subregions across the US based on actual historical electricity prices and the generation mix for the year 2016. Results show that storage increases the coal generation and affects the natural gas generation in the west – except in California and the Midwest regions of the US; and increases the generation of the natural gas in the eastern US regions. California, upstate New York and New England regions show an exception with an increase in natural gas generation and decrease in coal generation. The model also investigates the operational effects of storage on the profits of other generating units in California, Midwest and New York regions. Profits of other generating units are significantly affected when large capacities of storage operate as price-makers. Coal has a small increase in profits by 2% and all the other fuels continue to see a decline in profits in New York and the Midwest regions. The decrease in profits of the other generating units is because of the offset/retirements of the peaker natural gas plants that set the electricity prices. On the other hand, in California, the profits for renewables increase from the increase in electricity clearing prices set by the natural gas combined cycle plants to meet the additional demand from the storage charging

Superconducting Digital Logic Families Using Quantum Phase-slip Junctions

Superconducting electronics based computing is being actively pursued as an alternative to CMOS-based computing for high performance computing due to their inherent advantages such as low-power and high switching speed. These circuits are predominantly based on Josephson junctions. In this work, superconducting digital electronic circuits based on a device called quantum phase-slip junction are explored. Quantum phase-slip junctions are dual to Josephson junctions based on charge-flux duality of Maxwell's equations. Therefore, incorporating these devices into superconducting computers could lead to certain advantages that may overcome some of the challenges currently faced by Josephson junction based circuits, as explained in later chapters in this document. Three different superconducting logic circuit families are introduced using quantum phase-slip junctions and Josephson junctions, namely charge-based logic family, complementary quantum logic family and adiabatic quantum charge parametron logic family, with different advantages and challenges for each of the circuit families. The various circuits comprising these logic families have been demonstrated using circuit simulations in a program called WRSPICE. For this purpose, a SPICE model has been developed for quantum phase-slip junctions that can be loaded into WRSPICE. Charge-based logic family using quantum-phase-slip junctions is inspired from single-flux quantum family based on Josephson junctions. The presence or absence of a single charge pulse (i.e. a current pulse of a constant area equal to $2e$ where $e$ is the charge of an electron, generated by switching a quantum phase-slip junction) constitutes the logical bit $1$ and $0$ respectively. Several circuits in this logic family are exact dual versions of single-flux quantum family, while several additional circuits are designed that are exclusive to charge-based logic family. It is comprised of logic gates such as AND, OR, XOR, NAND, NOR etc., and various data manipulation circuits such as buffer circuits, fan-out circuits and merger circuits. Complementary quantum logic family combines the charge-based logic with quantum phase-slip junctions and flux-based logic with Josephson junctions. Therefore, it consists of circuits that convert flux to charge and vice-versa. Additionally, a control circuit has been designed that has a gate input to turn the output signal ON or OFF. Logic and fan-out circuits have been demonstrated using circuit simulations that comprise of basic principles introduced in flux-charge conversion circuits and control circuit. Adiabatic quantum charge parametron family is a variation of charge-based logic family that when operated in a certain mode of operation allows switching from logical bit $1$ to $0$ and vice-versa while dissipating energy less than the thermal energy at that temperature. Therefore, these circuits are compatible with reversible computing. The switching energy calculations that correspond to the circuit parameters and its operating conditions required for adiabatic switching (i.e. when switching energy is below the thermal energy $K_BT$) are shown. Universal logic gates such as the Majority gate has been designed and demonstrated in simulation. Several examples that use Majority gate to achieve logic operations such as AND, OR, XOR etc. are shown. Theoretical calculations were performed based on existing physics models for quantum phase-slip junctions to extract the physical design parameters of the devices based on required circuit parameters according to simulation. Using the same calculations, materials suitable for these devices were estimated that provide highest probability of exhibiting quantum phase-slips. Additionally, the operating temperature of the circuit families introduced for several materials of interest are obtained from these calculations. The switching speeds versus power dissipation for varying device parameters are calculated and compared to existing superconducting technologies using Josephson junctions. The work presented in this dissertation is intended to generate interest in a new field of digital logic circuits using quantum phase-slip junctions, the devices that were not previously explored for use in classical computing systems. The new circuit families introduced exhibit several potential advantages over the existing circuits in terms of higher energy efficiency, faster switching speed as well as ease of operation that may lead to a possibility of higher integration density

Design optimization of tripod truss: SLP approach

The efficiency of sequential linear programming technique in optimizing nonlinear constrained structural optimization problems is studied in this paper considering tripod truss structure as a case study. The axial force in each of the members of the truss due to payload is estimated using vector mechanics. The problem is formulated for minimum weight considering localized buckling stress, Euler buckling stress and direct compressive stress as constraints. The structure is optimized considering mean diameter and payload height as design variables. The weight of the truss got reduced by 20.51%.The optimum values of design variables obtained are compared with the values obtained using graphical method. The optimum values of design variables obtained using both the approaches are in reasonable agreement with a mere 5.17% variation