Wide Range Of System Conditions Research Articles

Biological therapies and management of oral mucosal disease

Biologic drugs are drugs made by living organisms and the term is usually limited to monoclonal antibodies or receptors targeting specific cytokines or cells that have been developed in recent decades. These drugs have had an enormous impact on the management of cancers, including head and neck cancers, and immune-mediated inflammatory conditions, for example, rheumatoid arthritis and inflammatory bowel disease. General dental practitioners will routinely be managing patients who are on these medications for a wide range of systemic conditions. These drugs also have a limited role in the management of immune-mediated oral mucosal disease. In this article, we will introduce the range of biological agents and their systemic indications and then elaborate on their use in oral mucosal disease and the disadvantages associated with their use.

Adsorption of chalcophile metals onto thiol-based resins: Modeling adsorption capacity and behavior using surface complexation modeling

Adsorption of chalcophile metals from aqueous solution by thiol resins represents an efficient means of reusing these metals and remediating waste streams, and a predictive modeling approach is needed in order to design and optimize adsorption applications. In this study, potentiometric titration measurements, metal adsorption experiments and surface complexation modeling (SCM) approaches were used to characterize three thiol-based resins (BT40, SP70, and SP300), and to model their proton, Cd, Zn, and Pb adsorption capacities and behaviors. We find that the extent of Cd adsorption onto the three resins correlates strongly to the measured concentration of proton-active thiol sites on each resin, and that the BT40 resin has a significantly higher concentration of proton-active thiol sites than the other two resins tested. Using the BT40 as a model resin, we demonstrate that the measured stability constant (K) of the Cd-thiol surface complex on the resin successfully accounts for the effects of both the metal:resin ratio and pH over a wide range of experimental conditions. We also find that a linear free-energy relationship (LFER) exists between the K values of metal-thiol surface complexes on the BT40 resin and the K values of metal-thiol aqueous complexes for Cd, Zn and Pb. This LFER can be used to estimate the K values of other metal-thiol resin surface complexes that have not been measured experimentally, therefore enabling prediction of the adsorption behavior of a wide range of metals onto thiol-based resins under a wide range of system conditions. This study demonstrates that a SCM approach, coupled with potentiometric titration measurements and metal adsorption experiments, represents a powerful tool for the design and optimization of strategies for separating and recovering chalcophile metals from aqueous media.

Balancing Message Criticality and Timeliness in IoT Networks

We study the problem of balancing timeliness and criticality when gathering data from multiple sources using a two-level hierarchical approach. The devices that generate the data transmit them to a local hub. A central decision maker then has to decide which local hubs to allocate bandwidth to and the local hubs have to prioritize the messages they transmit when given the opportunity to do so. Whereas an optimal policy does exist for this problem such a policy would require global knowledge of messages at each local hub, rendering such a scheme impractical. We propose a distributed reinforcement-learning-based approach that accounts for both the timeliness requirements and criticality of messages. We evaluate our solution using a criticality-weighted deadline miss ratio as the performance metric. The performance analysis is done by simulating the behavior of the proposed policy as well as that of several natural policies under a wide range of system conditions. The results show that the proposed policy outperforms all the other policies - except for the optimal but impractical policy - under the range of system conditions studied and that in many cases it performs close (3% to 12% lower performance depending on the condition) to the optimal policy.

Secrecy Energy Efficiency of MIMOME Wiretap Channels With Full-Duplex Jamming

Full-duplex (FD) jamming transceivers recently have been shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this paper, we investigate whether FD jamming can also improve the system’s secrecy energy efficiency (SEE) in terms of securely communicated bits per Joule when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high signal-to-noise ratio (SNR), or for a bidirectional FD communication setup.

Thermodynamics of mixtures of patchy and spherical colloids of different sizes: A multi-body association theory with complete reference fluid information.

We present a theory to predict the structure and thermodynamics of mixtures of colloids of different diameters, building on our earlier work [A. Bansal et al., J. Chem. Phys. 145, 074904 (2016)] that considered mixtures with all particles constrained to have the same size. The patchy, solvent particles have short-range directional interactions, while the solute particles have short-range isotropic interactions. The hard-sphere mixture without any association site forms the reference fluid. An important ingredient within the multi-body association theory is the description of clustering of the reference solvent around the reference solute. Here we account for the physical, multi-body clusters of the reference solvent around the reference solute in terms of occupancy statistics in a defined observation volume. These occupancy probabilities are obtained from enhanced sampling simulations, but we also present statistical mechanical models to estimate these probabilities with limited simulation data. Relative to an approach that describes only up to three-body correlations in the reference, incorporating the complete reference information better predicts the bonding state and thermodynamics of the physical solute for a wide range of system conditions. Importantly, analysis of the residual chemical potential of the infinitely dilute solute from molecular simulation and theory shows that whereas the chemical potential is somewhat insensitive to the description of the structure of the reference fluid, the energetic and entropic contributions are not, with the results from the complete reference approach being in better agreement with particle simulations.

Optimal Joint Decoding of Correlated Data Over Orthogonal Multiple Access Channels with Memory

Motivated by the structure of basic sensor networks, we study an optimal joint decoding problem in which the real-valued outputs of two correlated Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying channel coding or interleaving, over a multiple-access channel that consists of two orthogonal point-to-point time-correlated Rayleigh fading subchannels used with soft-decision demodulation. Each fading subchannel is modeled by a nonbinary Markov noise discrete channel that was recently shown to effectively represent it. The correlated sources have memory captured by a time-varying correlation coefficient governed by a two-state first-order Markov process. At the receiver side, we design a joint sequence maximum a posteriori (MAP) decoder to exploit the correlation between the two sources, their temporal memory, and the redundancy left in the quantizers' indexes, the channels' soft-decision outputs, and noise memory. Under the simple practical case of using two-level source quantization, we propose a Markov model to estimate the joint behavior of the quantized sources. We then establish necessary and sufficient conditions under which the delay-prone joint sequence MAP decoder can be reduced to a simple instantaneous symbol-by-symbol decoder. We illustrate our analytical results by system simulation and demonstrate that joint MAP decoding can appropriately harness source and channel characteristics to achieve improved signal-to-distortion ratio performance for a wide range of system conditions.

Structure and thermodynamics of a mixture of patchy and spherical colloids: A multi-body association theory with complete reference fluid information.

A mixture of solvent particles with short-range, directional interactions and solute particles with short-range, isotropic interactions that can bond multiple times is of fundamental interest in understanding liquids and colloidal mixtures. Because of multi-body correlations, predicting the structure and thermodynamics of such systems remains a challenge. Earlier Marshall and Chapman [J. Chem. Phys. 139, 104904 (2013)] developed a theory wherein association effects due to interactions multiply the partition function for clustering of particles in a reference hard-sphere system. The multi-body effects are incorporated in the clustering process, which in their work was obtained in the absence of the bulk medium. The bulk solvent effects were then modeled approximately within a second order perturbation approach. However, their approach is inadequate at high densities and for large association strengths. Based on the idea that the clustering of solvent in a defined coordination volume around the solute is related to occupancy statistics in that defined coordination volume, we develop an approach to incorporate the complete information about hard-sphere clustering in a bulk solvent at the density of interest. The occupancy probabilities are obtained from enhanced sampling simulations but we also develop a concise parametric form to model these probabilities using the quasichemical theory of solutions. We show that incorporating the complete reference information results in an approach that can predict the bonding state and thermodynamics of the colloidal solute for a wide range of system conditions.

Inverse uncertainty quantification of trace physical model parameters using BFBT benchmark data

Forward quantification of simulation (code) response uncertainties requires knowledge of physical model parameter uncertainties. Nuclear thermal-hydraulics codes, such as RELAP5 and TRACE, do not provide any information on uncertainties of physical model parameters. A framework is developed to quantify uncertainties of physical model parameters using Maximum Likelihood Estimation (MLE), Bayesian Maximum A Priori (MAP), and Markov Chain Monte Carlo (MCMC) algorithms.The objective of the present work is to perform the sensitivity analysis of the physical model parameters in code TRACE and calculate their uncertainties using MLE, MAP, and MCMC algorithms. The OECD/NEA BWR Full-size fine-mesh Bundle Test (BFBT) data is used to quantify uncertainty of selected physical models of TRACE code. The BFBT is based on a multi-rod assembly with measured data available for single or two-phase pressure drop, axial and radial void fraction distributions, and critical power for a wide range of system conditions. In this work, the steady-state cross-sectional averaged void fraction distribution is used as the input data for inverse uncertainty quantification (IUQ) algorithms, and the selected physical model’s probability distribution function (PDF) is the desired output quantity.

Pressure Standards in Water Distribution Systems: Reflection on Current Practice with Consideration of Some Unresolved Issues

AbstractPressure standards assist in the design of water distribution systems and the assessment of their performance. Although exact thresholds are sometimes rather vague, unusually high and low pressures are widely understood to increase costs and put systems at risk from events like pipe bursts at the high-pressure end to the risk of contaminant intrusion or poor firefighting conditions at the low-pressure end. Interestingly, because the definition of what conditions constitute acceptable pressures differs around the world, a delivery pressure might be considered acceptable in some regions and unacceptable in others. But if a wider range of system conditions is considered, including transient events, an interesting question arises as to what exactly the standards might mean and how violations should be evaluated. Specifically, what kinds of pressure transgressions are most crucial to system performance and economics and what kinds are merely inconvenient? Certainly the issue of evaluating consequences ...

Experimental Investigation of Wall Nucleation Characteristics in Flow Boiling

Wall nucleation experiments have been performed in a vertical annulus test section for investigation of the bubble departure diameter and bubble departure frequency. The experimental data in forced convective subcooled boiling flow is presented as a parametric study of the effect of wall heat flux, local bulk liquid subcooling, liquid flow rate, and system pressure. The data are shown to extend the database currently available in literature to a wider range of system conditions. Along with the current database in forced convective flow, the available models for bubble departure size and frequency are reviewed and compared with the existing database. The prediction of the bubble departure frequency is shown to require accurate modeling of the bubble departure diameter which has poor agreement with the experimental database.

Effect of surface segregation and mobility on erosion of plasma-facing materials in magnetic fusion systems

The present work studies the combined effects of collisional sputtering and mixing processes of carbon impurities in tungsten plasma-facing material integrated with thermal processes including surface segregation and diffusion. We used our ITMC-DYN package, which includes description of all collisional and thermal processes, for the analysis of recent experimental results of tungsten erosion and carbon implantation at various target temperatures. Self-consistent integrated modeling predicted thermal processes effects on erosion/deposition dynamics and defined decisive parameters range and their importance. Critical parameters were estimated based on available experimental data. The integrated simulation reproduced the experimental results and predicted the transition from enhanced tungsten erosion to significant carbon coverage on the tungsten surface. These effects for wider range of system conditions with C/H ions irradiation and for reactor conditions can be predicted by including detailed modeling of chemical erosion processes in a self-consistent manner.

Studying the Maximum Instantaneous Non-Synchronous Generation in an Island System—Frequency Stability Challenges in Ireland

Synchronous island power systems, such as the combined Ireland and Northern Ireland power system, are facing increasing penetrations of renewable generation. As part of a wider suite of studies, performed in conjunction with the transmission system operators (TSOs) of the All-Island system (AIS), the frequency stability challenges at high and ultra-high wind penetrations were examined. The impact of both largest infeed loss and network fault induced wind turbine active power dips was examined: the latter contingency potentially representing a fundamental change in frequency stability risk. A system non-synchronous penetration (SNSP) ratio was defined to help identify system operational limits. A wide range of system conditions were studied, with results showing that measures such as altering ROCOF protection and enabling emulated inertia measures were most effective in reducing the frequency stability risk of a future Ireland system.

Uncertainty and sensitivity analyses as a validation tool for BWR bundle thermal–hydraulic predictions

In recent years, more realistic safety analyses of nuclear reactors have been based on best estimate (BE) computer codes. The need to validate and refine BE codes that are used in the predictions of relevant reactor safety parameters, led to the organization of international benchmarks based on high quality experimental data. The OECD/NRC BWR full-size fine-mesh bundle test (BFBT) benchmark offers a good opportunity to assess the accuracy of thermal–hydraulic codes in predicting, among other parameters, single and two phase bundle pressure drop, cross-sectional averaged void fraction distributions and critical powers under a wide range of system conditions. The BFBT is based on a multi-rod assembly integral test facility which is able to simulate the high pressure, high temperature fluid conditions found in BWRs through electrically heated rod bundles. Since code accuracy is unavoidably affected by models and experimental uncertainties, an uncertainty analysis is fundamental in order to have a complete validation study. In this paper, statistical uncertainty and sensitivity analyses are used to validate the thermal–hydraulic features of the POLCA-T code, based on a one dimensional model of the following macroscopic BFBT exercises: (1) single and two phase bundle pressure drop, (2) steady-state cross-sectional averaged void fraction, (3) transient cross-sectional averaged void fraction and (4) steady-state critical power tests. The Latin hypercube sampling (LHS) strategy was chosen since it densely stratifies across the range of each uncertain input probability distribution, allowing a much better coverage of the input uncertainties than simple random sampling (SRS). The results show that POLCA-T predictions on pressure drop and void fractions under a wide range of conditions are within the validation limits imposed by the uncertainty analysis, while the accuracy of critical power predictions depends much on the boundary and input conditions.

Restrained utilization of idleness for transparent scheduling of background tasks

A common practice in system design is to treat features intended to enhance performance and reliability as low priority tasks by scheduling them during idle periods, with the goal to keep these features transparent to the user. In this paper, we present an algorithmic framework that determines the schedulability of non-preemptable low priority tasks in storage systems. The framework estimates when and for how long idle times can be utilized by low priority background tasks, without violating pre-defined performance targets of user foreground tasks. The estimation is based on monitored system information that includes the histogram of idle times. This histogram captures accurately important statistical characteristics of the complex demands of the foreground activity. The robustness and the effectiveness of the proposed framework is corroborated via extensive trace driven simulations under a wide range of system conditions and background activities, and via experimentation on a Linux kernel 2.6.22 prototype.

Protection scheme for a distribution system with distributed generation using neural networks

Interconnection of distributed generation (DG) to a radial distribution system has some impacts on the coordination of protection devices. In this case, faults are fed by multi-sources; networks and DGs. Existence of multi-sources in fault condition is the main difficulty in the identification and location of faults and therefore distribution system protection. New protection methods should be introduced for isolation of faulted sections. This paper presents a novel approach that can overcome the above problems. A feed forward neural network is used to identify the fault location. The predicted results from the algorithm prove the effectiveness of the proposed procedure for identifying fault location and then protection of the system for a wide range of system conditions.

Performance of the optimal causal multicast algorithm: a statistical analysis

An optimal causal message ordering algorithm for asynchronous distributed systems was proposed by Kshemkalyani and Singhal and its optimality was proven theoretically. For a system of n processes, although the space complexity of this algorithm was shown to be O(n/sup 2/) integers, it was expected that the actual space overhead would be much less than n/sup 2/. It is difficult to determine the behavior of this algorithm by a theoretical analysis. We measure the overheads of two different implementations of the optimal causal message ordering algorithm via simulation under a wide range of system conditions. The optimal algorithm is seen to display significantly less message space overhead and log space overhead than the canonical Raynal-Schiper-Toueg algorithm.

Control of electric power systems

The increase in size and complexity of interconnected electric power systems, coupled with the industrial commitment to maximize security at a minimum cost, has led to the development of many special control devices. These control devices ensure that the electric power system is able to operate, without instability, under a wide range of system conditions. This article presents a tutorial overview of the basic concepts and techniques of control for stability in electric power systems. Emphasis is placed on the robustness of the overall electric power system along with modifications to the basic control necessary to achieve this robustness. Different stability concepts are illustrated and the associated stabilizing mechanisms and equipment are described. To facilitate the implementation of the stability criteria, models of power system components are described. Special considerations are then given to the tuning of the automatic voltage regulators and the associated analytical tools for steady-state regulation as well as small- and large-signal performance. Next, the issue of automatic generation control is critically examined before an efficient system-wide control scheme is presented. This scheme gurantees power system stability against any disturbance occuring anywhere in the power network. Some important topics like control during restoration, overvoltage control, new concepts in interconnected power system control, coordinated voltage control and artificial neural networks in power systems are discussed.

Application of branched pore diffusion model in the adsorption of reactive dyes on activated carbon

In this work, the branched pore diffusion model (BPDM) was applied to the single component adsorption of three reactive dyes on activated carbon in a batch stirred vessel. Results are in terms of theoretical concentration decay curves, characterised by the non-linear combination of four mass transfer parameters namely the external mass transfer coefficient k f, the solid diffusivity D s, the micropore rate coefficient k b and the fraction micropores f. An ‘improved’ solution technique was presented where an optimising subroutine was employed to select ‘best’ combination of the mass transfer parameters. Compared to the existing methods, this yielded more accurate results over a longer period of adsorption and shorter computational time. Also, equilibrium was accurately described by the Fritz–Schlünder isotherm. Results showed that, over a wide range of system conditions, a single k f, k b and f value described each dye/carbon system; while D s increased with the initial solution concentration, C 0. Furthermore, D s was mathematically related to the surface loading q s. This paper provides an in-sight into the relation between the sorbent surface, the solute properties and the adsorptive characterictics.

Optimum Microemulsions Formulated with Propoxylated Guerbet Alcohol and Propoxylated Tridecyl Alcohol Sodium Sulfates

Abstract This is a study of die phase behavior of Propoxylated Guerbet alcohol sodium sulfates C14EX(PO) and C16EX(PO) and Propoxylated tridecyl alcohol sodium sulfates C13(PO) using oil phase composition, water salinity and composition, temperature and propylene oxide number, PON, as variables, show the ability of these surfactants to generate optimum middle phase microemulsions. Optima were found for a wide range of system conditions, e.g. 2% to 16% electrolyte (including Ca++), 30° C to 80°C and octane to hexadecane for the oil phase.

Integrated decision making in a flexible assembly system: sensitivity analysis and extended testing

Abstract This paper presents the results of sensitivity analysis and e.Mendcd testing for a three-level flexible control strategy (FCS) in an assembly environment. The FCS, which includes product mix flexibility at the system level, product routeing flexibility at the cell level, and product sequencing flexibility at the machine level, is tested under a variety of system characteristics. The effects of lot size, buffer size, set-up times, product mix, process reliability and variability, and various policy interactions are considered. It is demonstrated that the three-level FCS provides robust improvement over assembly systems that do not incorporate the use of flexibility under a wide range of system conditions. This testing effort furthermore provides insight into the question of which system conditions may contribute to FCS effectiveness in general.