General Set Of Parameters Research Articles

Optimisation of gyrokinetic microstability using adjoint methods

Microinstabilities drive turbulent fluctuations in inhomogeneous, magnetised plasmas. In the context of magnetic confinement fusion devices, this leads to an enhanced transport of particles, momentum and energy, thereby degrading confinement. In this work, we describe an application of the adjoint method to efficiently determine variations of gyrokinetic linear growth rates on a general set of external parameters in the local $\delta f$ -gyrokinetic model. We then offer numerical verification of this approach. When coupled with gradient-based techniques, this methodology can facilitate the optimisation process for the microstability of the confined plasmas across a high-dimensional parameter space. We present a numerical demonstration wherein the ion-temperature-gradient instability growth rate in a tokamak plasma is minimised with respect to flux surface shaping parameters. The adjoint method approach demonstrates a significant computational speed-up compared with a finite-difference gradient calculation.

Plane polarisation in Comptonization process: A Monte Carlo study

Abstract High energies emissions observed in X-ray binaries (XRBs), active galactic nuclei (AGNs) are linearly polarised. The prominent mechanism for X-ray is the Comptonization process. We revisit the theory for polarisation in Compton scattering with unpolarised electrons and note that the ( $k \times k^{\prime}$ )-coordinate (in which, ( $k \times k^{\prime}$ ) acts as a z-axis, here k and k′ are incident and scattered photon momentum, respectively) is more convenient to describe it. Interestingly, for a fixed scattering plane the degree of polarisation PD after single scattering for randomly oriented low-energy unpolarised incident photons is $\sim$ 0.33. At the scattering angle $\theta$ = 0 or $\theta \equiv$ [0,25 $^{\circ}$ ], the modulation curve of k′ exhibits the same PD and PA (angle of polarisation) of k, and even the distribution of projection of electric vector of k′ ( $k^{\prime}_{e}$ ) on perpendicular plane to the k indicates same (so, an essential criteria for detector designing). We compute the polarisation state in Comptonization process using Monte Carlo methods with considering a simple spherical corona. We obtain the PD of emergent photons as a function of $\theta$ -angle (or alternatively, the disc inclination angle i) on a meridian plane (i.e. the laws of darkening, formulated by Chandrasekhar (1946, ApJ, 103, 351) after single scattering with unpolarised incident photons. To explore the energy dependency we consider a general spectral parameter set corresponding to hard and soft states of XRBs, we find that for average scattering no. $\langle N_{sc}\rangle$ $\sim$ 1.1 the PD is independent of energy and PA $\sim 90^{\circ}$ ( $k^{\prime}_{e}$ is parallel to the disc plane), and for $\langle N_{sc}\rangle$ $\sim$ 5 the PD value is maximum for $i=45^{\circ}$ . We also compare the results qualitatively with observation of IXPE for five sources.

Data-Driven Model to Predict Aircraft Vibration Environment

Vibration levels that onboard equipment must be able to withstand throughout their lives for correct operation are mainly determined experimentally because predicting the dynamic behavior of a complete aircraft requires computational means and methods that are currently difficult to implement. We present a data-driven methodology that leverages flight-test accelerometer data to produce a predictive model. This model, based on an ensemble of artificial neural networks, performs a multioutput multivariate regression to estimate vibration spectra from a set of aircraft general parameters without having to characterize excitation sources. The model is compared with baseline models over two protocols, which are 1) standard training and testing as well as 2) extrapolation to high dynamic pressures, in order to assess physical consistency. Although the first protocol shows that all models can produce results accurate enough for this context, the second protocol shows that only the ensemble model is able to correctly extrapolate the energy. Using the Shapley additive explanations method, also known as SHAP, we show that these results can be explained by the ability of our model to identify the dynamic pressure as the core feature used in the extrapolation protocol. The proposed model can be used in multiple applications, such as anomaly detection and vibration flight envelope opening.

Research on Dynamic Modeling and Parameter Identification of the Grid-Connected PV Power Generation System

With the increasing proportion of renewable energy in the new power system, the grid-connected capacity of photovoltaic (PV) units shows an obvious upward trend, but its dynamic behavior under different penetration rates significantly affects the transient stability of the power system, so it is crucial to establish a dynamic model that meets the actual working conditions and select a suitable parameter identification method. Therefore, in this paper, based on the electromechanical transient characteristics of the grid-connected PV power generation system, the corresponding dynamic discrete equivalent model is established, and the simulation platform of the grid-connected PV power generation system is built in MATLAB/Simulink to study the adaptability of the dynamic discrete equivalent model of the grid-connected PV power generation system from the single and multiple scenarios using the ordinary least squares (OLS) and bat algorithm (BA) while comparing the generalization ability of the parameters identified by the two methods to the model. The simulation results show that the generalization ability of the parameters identified by the OLS and BA for the model in the single scenario is better, indicating that the model has good adaptability; the generalization ability of a set of general parameters identified by the BA for the model in the multiple scenarios is better than that of the OLS, indicating that the parameters identified by the BA have better adaptability. In conclusion, the dynamic discrete equivalent model of the grid-connected PV power generation system proposed in this paper can accurately reflect the dynamic characteristics of the grid-connected PV power generation system, and the parameters identified by the BA are more generalized than the OLS.

SO(4) multicriticality of two-dimensional Dirac fermions

We study quantum multicritical behavior in a (2+1)-dimensional Gross-Neveu-Yukawa field theory with eight-component Dirac fermions coupled to two triplets of order parameters that act as Dirac masses, and transform as $(1,0) + (0,1)$ representation under the SO(4)$\simeq$SO(3)$\times$SO(3) symmetry group. This field theory is relevant to spin-1/2 fermions on honeycomb or $\pi$-flux lattices, for example, near the transition points between an $s$-wave superconductor and a charge-density wave, on one side, and N\'eel order, on the other. Two triplets of such order parameters always allow for a common pair of two other order parameters that would complete them to the maximal set of compatible (anticommuting) orders of five. We first derive a unitary transformation in the Nambu (particle-hole) space which maps any two such triplets, possibly containing some superconducting orders, onto purely insulating order parameters. This allows one to consider a universal SO(4) Gross-Neveu-Yukawa description of the multicriticality without any Nambu doubling. We then proceed to derive the renormalization-group flow of the coupling constants at one-loop order in $4-\epsilon$ space-time dimensions, allowing also a more general set of order parameters transforming under SO($n_a$)$\times$SO($n_b$). While for $n_a=n_b > 2 $ in the bosonic sector and with fermions decoupled there is a stable fixed point of the flow, the Yukawa coupling to fermions quickly leads to its elimination by a generic fixed-point collision in the relevant range of fermion flavor numbers $N_f$. This suggests the replacement of the critical behavior by a runaway flow in the physical case $n_a=n_b=3$. The structure of the RG flow at $n_a\neq n_b$ is also discussed, and some non-perturbative arguments in favor of the stability of the decoupled critical point when $n_a=3$ and $n_b=1$ in $D=2+1$ are provided.

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids.

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.

Multipolar electrostatics for hairpin and pseudoknots in RNA: Improving the accuracy of force field potential energy function.

Molecular dynamics (MD) simulations that rely on force field methods has been widely used to explore the structure and function of RNAs. However, the current commonly used force fields are limited by the electrostatic description offered by atomic charge, dipole and at most quadrupole moments, failing to capture the anisotropic picture of electronic features. Actually, the distribution of electrons around atomic nuclei is not spherically symmetric but is geometry dependent. A multipolar electrostatic model based on high rank multipole moments is described in this work, which allows us to combine polarizability and anisotropy of electron density. RNA secondary structure was taken as a research system, and its substructures including stem, loops (hairpin loop, bulge loop, internal loop, and multi-branch loop), and pseudoknots (H-type and K-type) were investigated, respectively, as well as the hairpin. First, the atom-atom electrostatic properties derived from one chain of a duplex RNA 2MVY in our previous work (Ref. 58) were measured by the pilot RNA systems of hairpin, hairpin loop, stem, and H-type pseudoknot, respectively. The prediction results were not satisfactory. Consequently, to obtain a general set of electrostatic parameters for RNA force fields, the convergence behavior of the atom-atom electrostatic interactions in the pilot RNA systems was explored using high rank atomic multipole moments. The pilot RNA systems were cut into four types of different-sized molecular fragments, and the single nucleotide fragment and nucleotide-paired fragment proved to be the most reasonable systems for base-unpairing regions and base-pairing regions to investigate the convergence behavior of all types of atom-atom electrostatic interactions, respectively. Transferability of the electrostatic properties drawn from the pilot RNA systems to the corresponding test systems was also investigated. Furthermore, the convergence behavior of atomic electrostatic interactions in other substructures including bulge loop, internal loop, multi-branch loop, and K-type pseudoknot was expected to be modeled via the hairpin.

Performance Analysis of Non-uniform Sparse Segmentation Integral Method Based on Gauss Integral in EM Forward of Electrical Antenna Under Stratified Ocean

In order to solve the problem that it is difficult to take into account the computational efficiency and accuracy of electromagnetic field froward modeling of electrical antenna under the stratified ocean, evaluate the performance of two non-uniform sparse segmentation integral calculation methods based on Gauss integrals and improve the efficiency and accuracy of data interpretation in engineering applications, firstly two non-uniform sparse segmentation calculation methods based on Gauss integral nodes (Gauss-Legendre integral nodes and Gauss-Chebyshev integral nodes) are introduced. Then, two fast numerical integration methods corresponding of the time and frequency domain of the electrical antenna electromagnetic field under stratified ocean is established. Finally, by comparing and analyzing the results of the traditional uniform dense segmentation numerical integral calculation from the two aspects of computational accuracy and efficiency, the results show that two non-uniform sparse segmentation integral methods can improve the computational efficiency under the condition that the calculation accuracy is comparable, and the non-uniform sparse integral calculation method based on the Gauss-Chebyshev integral nodes is more significant than the calculation efficiency performance of the method based on the Gauss-Legendre integral node. At the same time, the general parameter setting of the non-uniform sparse segmentation integral method is given in this paper.

Analytical modeling electrical conduction in resistive-switching memory through current-limiting-friendly combination frameworks

Resistive-switching memory (RSM) is one of the most promising candidates for next-generation edge computing devices due to its excellent device performance. Currently, a number of experimental and modeling studies have been reported to understand the conduction behaviors. However, a complete physical picture that can describe the conduction behavior is still missing. Here, we present a conduction model that not only fully accounts for the rich conduction behaviors of RSM devices by harnessing a combination of electronic and thermal considerations via electron mobility and trap-depth and with excellent accuracy but also provides critical insight for continued design, optimization, and application. A physical model that is able to describe both the conduction and switching behaviors using only a single set of expressions is achieved. The proposed model reveals the role of temperature, mobility of electrons, and depth of traps, and allows accurate prediction of various set and reset processes obtained by an entirely new set of general current-limiting parameters.

Psychological design of educational-book complexes as orgtechnological means of module-developmental interaction

The article substantiates the idea of psychological designing of an innovative educational-book complex (EBC) as a psychodidactic tool of educational process’ subjects and at the same time a quasi-subject of polydialogical educational interaction. It is a subject of versatile cognition and is studied from the standpoints of different methodological approaches – systemic, activity, task, communicative, humanistic, socio-cultural and vitacultural. In the framework of the last approach theoretically are substantiates, on the one hand, an integrated model of the process of designing educational books, as the result of which element-by-element fullness of its main stages is achieved and an exhaustive list of regulatory requirements, factors and conditions for their effective implementation is stated, and on the other hand - an innovative EBC as an object of psychological-didactic cognition, scientific design, innovative construction, and in the following stages as a subject of complex examination and experimental introduction into the educational process. Thus, the theory, methodology and technology of psychologically expedient construction of EBC content and structure as a set of general principles, features, parameters and indicators are systematically presented, that take into account age-old psychological patterns, as well as individual-typological peculiarities of psycho-spiritual development and personal-professional growth of students. The study substantiates the system of EBC functions, which are grouped according to the following criteria: a) a carrier of educational content, b) a factor of the development of mental processes, states, properties and tendencies, c) an organizer of processes of self-learning and self-education; d) a means of involving personality n continuous cultural formation through immersion into the sphere of human experience and his internal psycho-spiritual self-liberation. In this context, four macrostructural components of this complex, which form a coherent system and are designed simultaneously, are argued: 1) a thesaurus or dictionary, 2) a tutorial, 3) a module-developmental textbook, and 4) an educational program for self-realization of the student’s personality. The proposed set of tools implements the psychological mechanism of human mastering the information and, most importantly, the organizational technology of implementing a holistic educational cycle in the module-developmental training system, which involves implementation of each internally acceptable trajectory of self-development. In this regard, the orgtechnological sequence of psychological design of innovative EBCs is proposed, which covers four periods and nine derivative stages, according to which the system of principles and nomenclature of psychological requirements for the content and structure of educational publications for adolescents is developed. Also, based on the modern scientific achievements in the field of semiotics, psychological hermeneutics, psycholinguistics, psychosemantics and psychoidactics, the model of interaction between the reader and the structured content of the specified complex is developed, which covers the forms of fixation, stages of processing socio-culturally determined information and mechanisms of mutual transition of the last one into the corresponding processes and subjective meanings-images of personal knowledge. A psychodiagnostic methodic was developed and successfully tested for the first time, aimed at identifying students’ level of realization of their own psychological potential (mental processes, states, properties and tendencies) based on their interaction with the educational literature. Thanks to this technique, which covers 432 positive and negative indicators of the EBC content and structure, there is an ability to objectively express in a single digit the level of its developmental effectiveness as a multicomponent innovative toolkit. Much higher level of psycho-didactic quality and psychological efficiency of using innovative EBCs is empirically argued in comparison with traditional educational books. Along with that, a direct linear relationship between the student’s academic achievement and the level of formation of their informative-cognitive skills of work (application of adequate reading strategies, algorithms, operations, techniques) with educational books were revealed by means of correlation analysis.

Generic parameters of first-order kinetics accurately describe soil organic matter decay in bare fallow soils over a wide edaphic and climatic range

The conventional soil organic matter (SOM) decay paradigm considers the intrinsic quality of SOM as the dominant decay limitation with the result that it is modelled using simple first-order decay kinetics. This view and modelling approach is often criticized for being too simplistic and unreliable for predictive purposes. It is still under debate if first-order models can correctly capture the variability in temporal SOM decay observed between different agroecosystems and climates. To address this question, we calibrated a first-order model (Q) on six long-term bare fallow field experiments across Europe. Following conventional SOM decay theory, we assumed that parameters directly describing SOC decay (rate of SOM quality change and decomposer metabolism) are thermodynamically constrained and therefore valid for all sites. Initial litter input quality and edaphic interactions (both local by definition) and microbial efficiency (possibly affected by nutrient stoichiometry) were instead considered site-specific. Initial litter input quality explained most observed kinetics variability, and the model predicted a convergence toward a common kinetics over time. Site-specific variables played no detectable role. The decay of decades-old SOM seemed mostly influenced by OM chemistry and was well described by first order kinetics and a single set of general kinetics parameters.

MNL-Bandit: A Dynamic Learning Approach to Assortment Selection

We consider a dynamic assortment selection problem where in every round the retailer offers a subset (assortment) of N substitutable products to a consumer, who selects one of these products according to a multinomial logit (MNL) choice model. The retailer observes this choice, and the objective is to dynamically learn the model parameters while optimizing cumulative revenues over a selling horizon of length T. We refer to this exploration–exploitation formulation as the MNL-Bandit problem. Existing methods for this problem follow an explore-then-exploit approach, which estimates parameters to a desired accuracy and then, treating these estimates as if they are the correct parameter values, offers the optimal assortment based on these estimates. These approaches require certain a priori knowledge of “separability,” determined by the true parameters of the underlying MNL model, and this in turn is critical in determining the length of the exploration period. (Separability refers to the distinguishability of the true optimal assortment from the other suboptimal alternatives.) In this paper, we give an efficient algorithm that simultaneously explores and exploits, without a priori knowledge of any problem parameters. Furthermore, the algorithm is adaptive in the sense that its performance is near optimal in the “well-separated” case as well as the general parameter setting where this separation need not hold.

Optimal growth in the Robinson-Shinkai-Leontief model: the case of capital-intensive consumption goods

Abstract We study the two-sector Robinson-Shinkai-Leontief (RSL) model of discrete-time optimal economic growth for the case of capital-intensive consumption goods. We frame the model in the context of Nishimura’s oeuvre, and more specifically, relate it to its neoclassical cousin: the Uzawa-Srinivasan continuous-time version studied in Haque, W. 1970. “Sceptical Notes on Uzawa’s ‘Optimal Growth in a Two-Sector Model of Capital Accumulation’, and a Precise Characterization of the Optimal Path.” The Review of Economic Studies 37: 377–394. We take Fujio’s identification of the marginal rate of transformation ζ of capital goods today into capital goods tomorrow (Fujio, M. 2006. Optimal Transition Dynamics in the Leontief Two-Sector Growth Model. Ph.D. thesis, The Johns Hopkins University), and using a mix of the Bellman-Blackwell methods of dynamic programming and the value-loss approach of Brock-Mitra, pin down the optimal policy for a specific subset of the parameter space. We discern a bifurcation pattern with respect to the discount factor that echoes the results of Benhabib, J., and K. Nishimura. 1979. “The Hopf Bifurcation and the Structure and Stability of Closed Orbits with Heterogeneous Steady States in Multi-Sector Models of Optimal Growth.” Journal of Economic Theory 21: 421–444 for the neoclassical model, and Khan, M. A., and T. Mitra. 2005. “On Choice of Technique in the Robinson-Solow-Srinivasan Model.” International Journal of Economic Theory 1: 83–110 for the RSS model. We also study the optimal policy correspondence for a general parameter set.

Performance Evaluation of Fixed Sample Entropy in Myographic Signals for Inspiratory Muscle Activity Estimation.

Fixed sample entropy (fSampEn) has been successfully applied to myographic signals for inspiratory muscle activity estimation, attenuating interference from cardiac activity. However, several values have been suggested for fSampEn parameters depending on the application, and there is no consensus standard for optimum values. This study aimed to perform a thorough evaluation of the performance of the most relevant fSampEn parameters in myographic respiratory signals, and to propose, for the first time, a set of optimal general fSampEn parameters for a proper estimation of inspiratory muscle activity. Different combinations of fSampEn parameters were used to calculate fSampEn in both non-invasive and the gold standard invasive myographic respiratory signals. All signals were recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing, thus allowing the performance of fSampEn to be evaluated for a variety of inspiratory muscle activation levels. The performance of fSampEn was assessed by means of the cross-covariance of fSampEn time-series and both mouth and transdiaphragmatic pressures generated by inspiratory muscles. A set of optimal general fSampEn parameters was proposed, allowing fSampEn of different subjects to be compared and contributing to improving the assessment of inspiratory muscle activity in health and disease.

Solvent-Aware Interfaces in Continuum Solvation.

Continuum models to handle solvent and electrolyte effects in an effective way have a long tradition in quantum-chemistry simulations and are nowadays also being introduced in computational condensed-matter and materials simulations. A key ingredient of continuum models is the choice of the solute cavity, i.e., the definition of the sharp or smooth boundary between the regions of space occupied by the quantum-mechanical (QM) system and the continuum embedding environment. The cavity, which should really reflect the region of space accessible to the degrees of freedom of the environmental components (the solvent), is usually defined by an exclusion approach in terms of the degrees of freedom of the system (the solute), typically, the atomic position of the QM system or its electronic density. Although most of the solute-based approaches developed lead to models with comparable and high accuracy when applied to small organic molecules, they can introduce significant artifacts when complex systems are considered. As an example, condensed-matter simulations often deal with supports that present open structures, i.e., low-density materials that have regions of space in which a continuum environment could penetrate, while a real solvent would not be able to. Similarly, unphysical pockets of continuum solvent may appear in systems featuring multiple molecular components, e.g., when dealing with hybrid QM/continuum approaches to solvation that involve introducing explicit solvent molecules around the solvated system. Here, we introduce a solvent-aware approach to eliminate the unphysical effects where regions of space smaller than the size of a single solvent molecule could still be filled with a continuum environment. We do this by defining a smoothly varying solute cavity that overcomes several of the limitations of straightforward solute-based definitions. This new approach applies to any smooth local definition of the continuum interface, it being based on the electronic density or the atomic positions of the QM system. It produces boundaries that are continuously differentiable with respect to the QM degrees of freedom, leading to accurate forces and/or Kohn-Sham potentials. The additional parameters involved in the solvent-aware interfaces can be set according to geometrical principles or can be converged to improve accuracy in complex multicomponent systems. Benchmarks on semiconductor substrates and on explicit water substrates confirm the flexibility and the accuracy of the approach and provide a general set of parameters for condensed-matter systems featuring open structures and/or explicit liquid components.

Centralized Repair of Multiple Node Failures With Applications to Communication Efficient Secret Sharing

This paper considers a distributed storage system, where multiple storage nodes can be reconstructed simultaneously at a centralized location. This centralized multi-node repair (CMR) model is a generalization of regenerating codes that allow for bandwidth efficient repair of a single-failed node. This paper focuses on the tradeoff between the amount of data stored and repair bandwidth in the CMR model. In particular, repair bandwidth bounds are derived for the minimum storage multi-node repair (MSMR) and the minimum bandwidth multi-node repair (MBMR) operating points. The tightness of these bounds is analyzed via code constructions. The MSMR point is characterized by codes achieving this point under functional repair for the general set of CMR parameters, as well as with codes enabling exact repair for certain CMR parameters. The MBMR point, on the other hand, is characterized with exact repair codes for all CMR parameters for systems that satisfy a certain entropy accumulation property. Finally, the model proposed here is utilized for the secret sharing problem, where the codes for the multi-node repair problem are used to construct communication efficient secret sharing schemes with the property of bandwidth efficient share repair.

A maximally particle-hole asymmetric spectrum emanating from a semi-Dirac point

Tight binding models have proven an effective means of revealing Dirac (massless) dispersion, flat bands (infinite mass), and intermediate cases such as the semi-Dirac (sD) dispersion. This approach is extended to a three band model that yields, with chosen parameters in a two-band limit, a closed line with maximally asymmetric particle-hole dispersion: infinite mass holes, zero mass particles. The model retains the sD points for a general set of parameters. Adjacent to this limiting case, hole Fermi surfaces are tiny and needle-like. A pair of large electron Fermi surfaces at low doping merge and collapse at half filling to a flat (zero energy) closed contour with infinite mass along the contour and enclosing no carriers on either side, while the hole Fermi surface has shrunk to a point at zero energy, also containing no carriers. The tight binding model is used to study several characteristics of the dispersion and density of states. The model inspired generalization of sD dispersion to a general ± form, for which analysis reveals that both n and m must be odd to provide a diabolical point with topological character. Evolution of the Hofstadter spectrum of this three band system with interband coupling strength is presented and discussed.

A systematic methodology to extend the applicability of a bioconversion model for the simulation of various co-digestion scenarios

Detailed simulation of anaerobic digestion (AD) requires complex mathematical models and the optimization of numerous model parameters. By performing a systematic methodology and identifying parameters with the highest impact on process variables in a well-established AD model, its applicability was extended to various co-digestion scenarios. More specifically, the application of the step-by-step methodology led to the estimation of a general and reduced set of parameters, for the simulation of scenarios where either manure or wastewater were co-digested with different organic substrates. Validation of the general parameter set involved the simulation of laboratory-scale data from three continuous co-digestion experiments, treating mixtures of different organic residues either at thermophilic or mesophilic conditions. Evaluation of the results showed that simulations using the general parameter set fitted experimental data quite well, indicating that it offers a reliable reference point for future simulations of anaerobic co-digestion scenarios.

Activated Sludge Production Parameters and Nutrient Content of Organic Sludge Components.

An important part of biological treatment system design is quantifying the sludge production and the nutrient removal capacity. Influent wastewater COD fractionation, biomass growth and endogenous respiration directly impacts the composition of the mixed liquor solids in activated sludge systems. The objectives of this project were to determine the model kinetic and stoichiometric parameters associated with activated sludge production and the nutrient content (N and P) of unbiodegradable organic matter components. A complete sludge retention experiment was conducted over 70 days in a pilot-scale membrane bioreactor fed with a real municipal wastewater, and operated with alternating growth and famine periods. Experimental results were simulated and compared using the default values from two well-accepted model parameter sets. The General ASDM parameter set was found to better fit the experimental data than the Metcalf and Eddy parameter set, mainly to characterize endogenous respiration and the heterotrophic biomass concentration. An influent unbiodegradable organic particulate fraction (fXU,Inf) value of 0.16 g COD/g COD was determined by calibration of the accumulated sludge total COD, suspended solids and heterotrophic biomass concentrations. The nutrient content of the accumulated endogenous residue (XE) and influent unbiodegradable organic particulate (XU,Inf) components were calibrated to 0.030 and 0.100 g N/g COD and 0.035 and 0.008 g P/g COD, respectively. These values are in the range of those reported in the literature except for the high P content found in the endogenous residue, possibly due to the presence of coagulants added for P removal in the accumulated sludge. These results were consistent under the wide range of dynamic conditions tested and could improve model prediction of sludge production and composition.

General van der Waals potential for common organic molecules

This work presents a systematic development of a new van der Waals potential (vdW2016) for common organic molecules based on symmetry-adapted perturbation theory (SAPT) energy decomposition. The Buf-14-7 function, as well as Cubic-mean and Waldman–Hagler mixing rules were chosen given their best performance among other popular potentials. A database containing 39 organic molecules and 108 dimers was utilized to derive a general set of vdW parameters, which were further validated on nucleobase stacking systems and testing organic dimers. The vdW2016 potential is anticipated to significantly improve the accuracy and transferability of new generations of force fields for organic molecules.