First-principles calculations of binary Al compounds: Enthalpies of formation and elastic properties

Systematic first-principles calculations of energy vs. volume (E-V) and single crystal elastic stiffness constants (c_ij’s) have been performed for 50 Al binary compounds in the Al-X (X = Co, Cu, Hf, Mg, Mn, Ni, Sr, V, Ti, Y, and Zr) systems. The E-V equations of state are fitted by a four-parameter Birch-Murnaghan equation, and the c_ij’s are determined by an efficient strain-stress method. The calculated lattice parameters, enthalpies of formation, and c_ij’s of these binary compounds are compared with the available experimental data in the literature. In addition, elastic properties of polycrystalline aggregates including bulk modulus (B), shear modulus (G), Young’s modulus (E), B/G (bulk/shear) ratio, and anisotropy ratio are calculated and compared with the experimental and theoretical results available in the literature. The systematic predictions of elastic properties and enthalpies of formation for Al-X compounds provide an insight into the understanding and design of Al-based alloys.     

UNIQUENESS CONDITIONS OF CL-STRUCTURES IN GL-STRUCTURE EQUIVALENCE CLASSES OF SYSTEM RECONSTRUCTABILITY ANALYSIS

This paper first introduces the basic notions of overall systems with logical relations, their subsystems, structure representation graphs, sets of H-structures and G-structures with logical relations S _H ^L and S _G ^L, immediate refinement and aggregate with logical relations, structure-graph mappings r_V ^L, r_G ^L, etc., and the notions of inclusiveness with logical relations, upper bounding and lower bounding with logical relations. Then it proves the sufficient conditions under which representation graphs R ^L form a lattice. By defining the least upper bound and largest lower bound of (R^L, ) and recommending a lemma on distributivity, this paper proves the sufficient conditions under which G-structures with logical relations form Boolean lattices. Finally after defining the M-structures and C-structures with logical relations, i.e. M-structures and C-structures, this paper proposes the sufficient conditions for the uniqueness of C-structures in G-structure equivalence classes, and proves that the C ^L-structure is the least refined GL-structure in equivalence class S _G ^L/r _G ^L.     

Forest carbon densities and uncertainties from Lidar, QuickBird, and field measurements in California

Greenhouse gas inventories and emissions reduction programs require robust methods to quantify carbon sequestration in forests. We compare forest carbon estimates from Light Detection and Ranging (Lidar) data and QuickBird high-resolution satellite images, calibrated and validated by field measurements of individual trees. We conducted the tests at two sites in California: (1) 59 km² of secondary and old-growth coast redwood (Sequoia sempervirens) forest (Garcia-Mailliard area) and (2) 58 km² of old-growth Sierra Nevada forest (North Yuba area). Regression of aboveground live tree carbon density, calculated from field measurements, against Lidar height metrics and against QuickBird-derived tree crown diameter generated equations of carbon density as a function of the remote sensing parameters. Employing Monte Carlo methods, we quantified uncertainties of forest carbon estimates from uncertainties in field measurements, remote sensing accuracy, biomass regression equations, and spatial autocorrelation. Validation of QuickBird crown diameters against field measurements of the same trees showed significant correlation (r = 0.82, P < 0.05). Comparison of stand-level Lidar height metrics with field-derived Lorey's mean height showed significant correlation (Garcia-Mailliard r = 0.94, P < 0.0001; North Yuba R = 0.89, P < 0.0001). Field measurements of five aboveground carbon pools (live trees, dead trees, shrubs, coarse woody debris, and litter) yielded aboveground carbon densities (mean ± standard error without Monte Carlo) as high as 320 ± 35 Mg ha^− 1 (old-growth coast redwood) and 510 ± 120 Mg ha^− 1 (red fir [Abies magnifica] forest), as great or greater than tropical rainforest. Lidar and QuickBird detected aboveground carbon in live trees, 70-97% of the total. Large sample sizes in the Monte Carlo analyses of remote sensing data generated low estimates of uncertainty. Lidar showed lower uncertainty and higher accuracy than QuickBird, due to high correlation of biomass to height and undercounting of trees by the crown detection algorithm. Lidar achieved uncertainties of < 1%, providing estimates of aboveground live tree carbon density (mean ± 95% confidence interval with Monte Carlo) of 82 ± 0.7 Mg ha^− 1 in Garcia-Mailliard and 140 ± 0.9 Mg ha^− 1 in North Yuba. The method that we tested, combining field measurements, Lidar, and Monte Carlo, can produce robust wall-to-wall spatial data on forest carbon.     

Data distribution schemes of sparse arrays on distributed memory multicomputers

A data distribution scheme of sparse arrays on a distributed memory multicomputer, in general, is composed of three phases, data partition, data distribution, and data compression. To implement the data distribution scheme, many methods proposed in the literature first perform the data partition phase, then the data distribution phase, followed by the data compression phase. We called a data distribution scheme with this order as Send Followed Compress (SFC) scheme. In this paper, we propose two other data distribution schemes, Compress Followed Send (CFS) and Encoding-Decoding (ED), for sparse array distribution. In the CFS scheme, the data compression phase is performed before the data distribution phase. In the ED scheme, the data compression phase can be divided into two steps, encoding and decoding. The encoding step and the decoding step are performed before and after the data distribution phase, respectively. To evaluate the CFS and the ED schemes, we compare them with the SFC scheme. In the data partition phase, the row partition, the column partition, and the 2D mesh partition with/without load-balancing methods are used for these three schemes. In the compression phase, the CRS/CCS methods are used to compress sparse local arrays for the SFC and the CFS schemes while the encoding/decoding step is used for the ED scheme. Both theoretical analysis and experimental tests were conducted. In the theoretical analysis, we analyze the SFC, the CFS, and the ED schemes in terms of the data distribution time and the data compression time. In experimental tests, we implemented these three schemes on an IBM SP2 parallel machine. From the experimental results, for most of test cases, the CFS and the ED schemes outperform the SFC scheme. For the CFS and the ED schemes, the ED scheme outperforms the CFS scheme for all test cases.

On the structure of free finite state machines

The finite state machine U_{m, n}(M) freely generated by a set consisting of m states and n inputs subjects to the relations holding in the finite state machine M was considered by Birkhoff and Lipson in [1, 2]. In this paper, necessary and sufficient conditions for U_{m, n}(M) to consist of m disjoint copies of U_{1, n}(M) are established. The relationship between U_{1, n}(M) and the transition monoid of M, and a representation of U_{1, n}(M) as a transition monoid machine are described. The characterization of machines of type U_{1, n}(M) is in this way reduced to the characterization of finite monoids possessing a ‘universal presentation’. Some general results concerning finite semigroups and groups with a universal presentation, and precise characterizations of finite semilattices and Abelian groups admitting a universal presentation are described.     

Some q-rung orthopair uncertain linguistic aggregation operators and their application to multiple attribute group decision making

q-Rung orthopair fuzzy sets (q-ROFSs), originally presented by Yager, are a powerful fuzzy information representation model, which generalize the classical intuitionistic fuzzy sets and Pythagorean fuzzy sets and provide more freedom and choice for decision makers (DMs) by allowing the sum of the $q\mathrm{t}\mathrm{h}$ power of the membership and the $q\mathrm{t}\mathrm{h}$ power of the nonmembership to be less than or equal to 1. In this paper, a new class of fuzzy sets called q-rung orthopair uncertain linguistic sets (q-ROULSs) based on the q-ROFSs and uncertain linguistic variables (ULVs) is proposed, and this can describe the qualitative assessment of DMs and provide them more freedom in reflecting their belief about allowable membership grades. On the basis of the proposed operational rules and comparison method of q-ROULSs, several q-rung orthopair uncertain linguistic aggregation operators are developed, including the q-rung orthopair uncertain linguistic weighted arithmetic average operator, the q-rung orthopair uncertain linguistic ordered weighted average operator, the q-rung orthopair uncertain linguistic hybrid weighted average operator, the q-rung orthopair uncertain linguistic weighted geometric average operator, the q-rung orthopair uncertain linguistic ordered weighted geometric operator, and the q-rung orthopair uncertain linguistic hybrid weighted geometric operator. Then, some desirable properties and special cases of these new operators are also investigated and studied, in particular, some existing intuitionistic fuzzy aggregation operators and Pythagorean fuzzy aggregation operators are proved to be special cases of these new operators. Furthermore, based on these proposed operators, we develop an approach to solve the multiple attribute group decision making problems, in which the evaluation information is expressed as q-rung orthopair ULVs. Finally, we provide several examples to illustrate the specific decision-making steps and explain the validity and feasibility of two methods by comparing with other methods.     

Exploring the potential of leaf reflectance spectra for retrieving the leaf maximum carboxylation rate

The maximum carboxylation rate (V_cmax) is a key photosynthetic parameter that is determined by the leaf biochemistry and environmental conditions. Numerous studies have shown that plant biochemical, physiological and structural parameters can be estimated from reflectance spectra. Therefore, it is reasonable to assume that V_cmax can be spectrally determined. Here, we investigate the potential of leaf reflectance spectra for retrieving the maximum carboxylation rate of leaves. Measurements of leaf reflectance, carbon dioxide (CO₂) response curves, leaf chlorophyll-a + b (chl-a + b) etc., were made on 80 crop, shrub and tree leaves. Then, the leaf V_cmax,25 was linked to leaf biochemistry and spectral reflectance. A reliable relationship, with a coefficient of determination (R²) value of 0.75, was found between the leaf chl-a + b content and V_cmax,25. The leaf V_cmax,25 values were also significantly correlated with chl-a + b-sensitive spectral indices with the highest R² value that was found being 0.83 for the ratio spectral index (RSI) using reflectances at 1089 nm and 695 nm. Finally, multiple stepwise regression (MSR) and a partial least-squares regression (PLSR) modelling approach were used to estimate V_cmax,25 from leaf reflectances. The results confirmed that V_cmax,25 can be reliably estimated from leaf reflectance spectra and give an R² value >0.80. These findings show that leaf chl-a + b can be used as a proxy for leaf V_cmax,25 and that leaf V_cmax,25 can be spectrally determined using leaf reflectance data.     

Constructing a Tree from Homeomorphic Subtrees, with Applications to Computational Evolutionary Biology

This paper discusses how to count and generate strings that are ``distinct' in two senses: p -distinct and b -distinct. Two strings x on alphabet A and x' on alphabet A' are said to be p -distinct iff they represent distinct ``patterns'; that is, iff there exists no one—one mapping from A to A' that transforms x into x' . Thus aab and baa are p -distinct while aab and ddc are p -equivalent. On the other hand, x and x' are said to be b -distinct iff they give rise to distinct border (failure function) arrays: thus aab with border array 010 is b -distinct from aba with border array 001 . The number of p -distinct (resp. b -distinct) strings of length n formed using exactly k different letters is the [k,n] entry in an infinite p' (resp. b' ) array. Column sums p[n] and b[n] in these arrays give the number of distinct strings of length n . We present algorithms to compute, in constant time per string, all p -distinct (resp. b -distinct) strings of length n formed using exactly k letters, and we also show how to compute all elements p'[k,n] and b'[k,n] . These ideas and results have application to the efficient generation of appropriate test data sets for many string algorithms. Received December 21, 1995; revised April 28, 1997.     

Phase diagrams of Bi–Sb–Se–Te system

Bi–Sb–Se–Te is one of the most important material systems for thermoelectric applications. Phase diagrams of its constituent binary and ternary systems are reviewed and assessed. The Bi–Sb–Se–Te isothermal section tetrahedron at 400 °C and liquidus projection tetrahedron were proposed. Ternary compounds are only found in the Bi–Sb–Se system. There are eight three-phase regions at 400 °C and seven primary solidification phases in the Bi–Sb–Se system, including (Bi,Sb), (Bi₂)_m(Bi₂Se₃)_n, Bi₂Se₃, Se, Sb₂Se₃, Bi₃Sb₅Se₂, Bi₃Sb₁₂Se₁₅. In the Bi–Sb–Te system, there are four three-phase regions at 400 °C. The (Bi,Sb)₂Te₃ and (Bi,Sb) are continuous solid solutions. There are six primary solidification phases, including (Bi,Sb)₂Te₃, (Te), γ, δ, (Bi,Sb), and (Bi₂)_m(Bi₂Te₃)_n. In the Bi–Se–Te system, there is one three-phase region. (Bi₂)_m(Bi₂Se₃)_n and (Bi₂)_m(Bi₂Te₃)_n form a continuous solid solution phase at 400 °C. There are four primary solidification phases, including Bi, (Bi₂)_m(Bi₂(Se,Te)₃)_n, Bi₂(Se,Te)₃ and (Se,Te). In the Sb–Se–Te system, there are five three-phase regions and six primary solidification phases, including (Sb), δ-(Sb₂Te), γ-(SbTe), Sb₂Te₃, and (Se,Te). A wide range of (Bi,Sb)₂(Se,Te)₃ single-phase region was observed in the Bi–Sb–Se–Te quaternary system.     

Simplicial powers of graphs

In a graph, a vertex is simplicial if its neighborhood is a clique. For an integer k≥1, a graph G=(V_G,E_G) is the k-simplicial power of a graph H=(V_H,E_H) (H a root graph of G) if V_G is the set of all simplicial vertices of H, and for all distinct vertices x and y in V_G, xyE_G if and only if the distance in H between x and y is at most k. This concept generalizes k-leaf powers introduced by Nishimura, Ragde and Thilikos which were motivated by the search for underlying phylogenetic trees; k-leaf powers are the k-simplicial powers of trees. Recently, a lot of work has been done on k-leaf powers and their roots as well as on their variants phylogenetic roots and Steiner roots. For k≤5, k-leaf powers can be recognized in linear time, and for k≤4, structural characterizations are known. For k≥6, the recognition and characterization problems of k-leaf powers are still open. Since trees and block graphs (i.e., connected graphs whose blocks are cliques) have very similar metric properties, it is natural to study k-simplicial powers of block graphs. We show that leaf powers of trees and simplicial powers of block graphs are closely related, and we study simplicial powers of other graph classes containing all trees such as ptolemaic graphs and strongly chordal graphs.     

Influence of doping BiYO3 and Nb2O5 on PTCR characteristics of BaTiO3 thermistor ceramics

Nb₂O₅-doped (1 − x)Ba_0.96Ca_0.04TiO₃-xBiYO₃ (where x = 0.01, 0.02, 0.03 and 0.04) lead-free PTC thermistor ceramics were prepared by a conventional solid state reaction method. X-ray diffraction, scanning electron microscope, Agilent E4980A and resistivity-temperature measurement instrument, were used to characteristic the lattice distortion, microstructure, temperature dependence of permittivity and resitivity-temperature dependence. It was revealed that the tetragonality c/a of the perovskite lattice, the microstructure and the Curie temperature changed with the BiYO₃ content. In order to decrease the room temperature resistivity, the effect of Nb₂O₅ on the room temperature resistivity was also studied, and its optimal doping content was finally chosen as 0.2 mol%. The 0.97Ba_0.96Ca_0.04TiO₃-0.03BiYO₃-0.002Nb₂O₅ thermistor ceramic exhibited a low ρ_RT of 3.98 × 10³ Ω cm, a typical PTCR effect of ρ_max/ρ_min > 10³ and a T_c of 153 °C.     

FluorMODleaf: A new leaf fluorescence emission model based on the PROSPECT model

A new model of chlorophyll a fluorescence emission by plant leaves, FluorMODleaf, is presented. It is an extension of PROSPECT, a widely used leaf optical properties model that regards the leaf as a pile of N absorbing and diffusing elementary plates. In FluorMODleaf, fluorescence emission of an infinitesimal layer of thickness dx is integrated over the entire elementary plate. The fluorescence source function is based on the excitation spectrum of diluted isolated thylakoids and on the emission spectra of isolated photosystems, PSI and PSII, which are the main pigment-protein complexes involved in the initial stages of photosynthesis. Scattering within the leaf is produced by multiple reflections within and between elementary plates. The input variables of FluorMODleaf are: the number of elementary plates N, also called leaf structure parameter, the total chlorophyll content C_ab, the total carotenoid content C_cx, the equivalent water thickness C_w, and the dry matter content C_m (or leaf mass per area), as in the new PROSPECT-5, plus the σ_II/σ_I ratio referring to the relative absorption cross section of PSI and PSII, and the fluorescence quantum efficiency of PSI and PSII, τ_I and τ_II, that are introduced here as mean fluorescence lifetimes. The model, which considers the reabsorption of emitted light within the leaf, allows good quantitative estimation of both upward and downward apparent spectral fluorescence yield (ASFY) at different excitation wavelengths from 400 nm to 700 nm. It also emphasizes the role of scattering in fluorescence emission by leaves having high chlorophyll content.     

Bernstein-type operators which preserve polynomials

In this paper we present the sequence of linear Bernstein-type operators defined for f∈C[0,1] by B_n(f°τ⁻¹)°τ, B_n being the classical Bernstein operators and τ being any function that is continuously differentiable ∞ times on [0,1], such that τ(0)=0, τ(1)=1 and τ^′(x)>0 for x∈[0,1]. We investigate its shape preserving and convergence properties, as well as its asymptotic behavior and saturation. Moreover, these operators and others of King type are compared with each other and with B_n. We present as an interesting byproduct sequences of positive linear operators of polynomial type with nice geometric shape preserving properties, which converge to the identity, which in a certain sense improve B_n in approximating a number of increasing functions, and which, apart from the constant functions, fix suitable polynomials of a prescribed degree. The notion of convexity with respect to τ plays an important role.     

Phase Equilibrium studies in the system “FeO”–SiO2–Al2O3–CaO–MgO at 1200 °C and Po2 10-8atm

Iron oxides and silica are the major components of copper smelting slag. The oxides of aluminum, calcium and magnesium are also present in the slag that is introduced through copper concentrate, flux and refractories. Liquidus temperatures of the copper smelting slags are usually controlled by Fe/SiO₂. The concentrations of Al₂O₃, CaO and MgO, and FeO/Fe₂O₃ in the slag can also affect the liquidus temperatures where FeO/Fe₂O₃ is a function of oxygen partial pressure. High temperature equilibration under controlled oxygen partial pressure followed by quenching and electron probe microanalysis were used to determine the compositions of the liquid and solid phases at 1200 °C and Po₂ 10^-8 atm. The experimental results are presented in the forms of pseudo-ternary sections “FeO”-CaO-SiO₂ at fixed 2, 4 and 6 wt pct MgO, and 2 + 2, 4 + 4 and 6 + 6 wt pct MgO + Al₂O₃. Spinel and tridymite are the major primary phases in the composition range investigated. In addition, CaSiO₃, pyroxene, olivine, and melilite are also present. The isotherms in the spinel and tridymite primary phase fields move towards higher SiO₂ concentration directions with increasing CaO, Al₂O₃, and MgO concentrations. The experimentally determined results are compared with the FactSage calculations.     

Thermodynamic description of the Al-Li-Zn system

The Al-Li-Zn system was critically assessed using the CALPHAD technique. The solution phases (liquid, bcc, fcc and hcp) were described by the substitutional solution model. The compounds Al₂Li₃ and Al₄Li₉ in the Al-Li system had homogeneity ranges of Zn and were treated as (Al,Zn)₂Li₃ and (Al,Zn)₄Li₉ in the Al-Li-Zn system, respectively. The compounds αLi₂Zn₃, βLi₂Zn₃, αLi₂Zn₅, βLi₂Zn₅ and αLiZn₄ in the Li-Zn system had no solubility of the third component Al in the Al-Li-Zn system. A two-sublattice model (Al,Li,Zn)_0.2(Al,Li,Zn)_0.8 was applied to describe the compound βLiZn₄ in the Al-Li-Zn system in order to cope with the order-disorder transition between hexagonal close-packed solution (hcp-A3) and βLiZn₄ with the Mg-type structure. The ternary compound τ₂ with a NaTl-type structure (B32) had the same structure with the compounds AlLi in the binary Al-Li system and LiZn in the binary Li-Zn system. In the present work, the three compounds AlLi, LiZn and τ₂ were treated as one phase by a two-sublattice model (Al,Li,Zn)_0.5(Al,Li,Zn)_0.5 in order to cope with the order-disorder transition between B32(AlLi, LiZn and τ₂) and body-centered cubic solid solution (bcc-A2). The ternary intermetallic compounds τ₁ and τ₃ in the Al-Li-Zn system were treated as the formula Li(Al,Zn)₂ and (AlLi,Zn)Zn₃, respectively. A set of self-consistent thermodynamic parameters describing the Gibbs energy of each individual phase as a function of composition and temperature in the Al-Li-Zn system was obtained.     

A decomposition of Moran's I for clustering detection

The test statistics I_h, I_c, and I_n are derived by decomposing the numerator of the Moran's I test for high-value clustering, low-value clustering, and negative autocorrelation, respectively. Formulae to compute the means and variances of these test statistics are derived under a random permutation test scheme, and the p-values of the test statistics are computed by asymptotic normality. A set of simulations shows that test statistic I_h is likely to be significant only for high-value clustering, test statistic I_c is likely to be significant only for low-value clustering, and test statistic I_n is likely to be significant only for negatively correlated spatial structures. These test statistics were used to reexamine spatial distributions of sudden infant death syndrome in North Carolina and the pH values of streams in the Great Smoky Mountains. In both analyses, low-value clustering and high-value clustering were shown to exit simultaneously.     

Robust non‐fragile H ∞ ∕ L2 − L ∞ control of uncertain linear system with time‐delay and application to vehicle active suspension

This paper presents an approach to design robust non‐fragile H _∞ ∕ L₂ ? L _∞ static output feedback controller, considering actuator time‐delay and the controller gain variations, and it is applied to design vehicle active suspension. According to suspension design requirements, the H _∞ and L₂ ? L _∞ norms are used, respectively, to reflect ride comfort and time‐domain hard constraints. By employing a delay‐dependent Lyapunov function, existence conditions of delay‐dependent robust non‐fragile static output feedback H _∞ controller and L₂ ? L _∞ controller are derived, respectively, in terms of the feasibility of bilinear matrix inequalities. Then, a new procedure based on LMI optimization and a hybrid algorithm of the particle swarm optimization and differential evolution is used to solve an optimization problem with bilinear matrix inequality constraints. Simulation results show that the designed active suspension system still can guarantee their own performance in spite of the existence of the model uncertainties, the actuator time‐delay and the controller gain variations. Copyright © 2014 John Wiley & Sons, Ltd.     

Estimation of distributions involving unobservable events: the case of optimal search with unknown Target Distributions

We consider the problem of estimating the parameters of a distribution when the underlying events are themselves unobservable. The aim of the exercise is to perform a task (for example, search a web-site or query a distributed database) based on a distribution involving the state of nature, except that we are not allowed to observe the various “states of nature” involved in this phenomenon. In particular, we concentrate on the task of searching for an object in a set of N locations (or bins) {C ₁, C ₂,…, C _N }, in which the probability of the object being in the location C _i is p _i , where P = [p ₁, p ₂,…, p _N ] ^T is called the Target Distribution. Also, the probability of locating the object in the bin within a specified time, given that it is in the bin, is given by a function called the Detection function, which, in its most common instantiation, is typically, specified by an exponential function. The intention is to allocate the available resources so as to maximize the probability of locating the object. The handicap, however, is that the time allowed is limited, and thus the fact that the object is not located in bin C _i within a specified time does not necessarily imply that the object is not in C _i . This problem has applications in searching large databases, distributed databases, and the world-wide web, where the location of the files sought for are unknown, and in developing various military and strategic policies. All of the research done in this area has assumed the knowledge of the {p _i }. In this paper we consider the problem of obtaining error bounds, estimating the Target Distribution, and allocating the search times when the {p _i } are unknown. To the best of our knowledge, these results are of a pioneering sort - they are the first available results in this area, and are particularly interesting because, as mentioned earlier, the events concerning the Target Distribution, in themselves, are unobservable.

Efficient mutual nearest neighbor query processing for moving object trajectories

Given a set D of trajectories, a query object q, and a query time extent Γ, a mutual (i.e., symmetric) nearest neighbor (MNN) query over trajectories finds from D, the set of trajectories that are among the k₁ nearest neighbors (NNs) of q within Γ, and meanwhile, have q as one of their k₂ NNs. This type of queries is useful in many applications such as decision making, data mining, and pattern recognition, as it considers both the proximity of the trajectories to q and the proximity of q to the trajectories. In this paper, we first formalize MNN search and identify its characteristics, and then develop several algorithms for processing MNN queries efficiently. In particular, we investigate two classes of MNN queries, i.e., MNN_P and MNN_T queries, which are defined with respect to stationary query points and moving query trajectories, respectively. Our methods utilize the batch processing and reusing technology to reduce the I/O cost (i.e., number of node/page accesses) and CPU time significantly. In addition, we extend our techniques to tackle historical continuous MNN (HCMNN) search for moving object trajectories, which returns the mutual nearest neighbors of q (for a specified k₁ and k₂) at any time instance of Γ. Extensive experiments with real and synthetic datasets demonstrate the performance of our proposed algorithms in terms of efficiency and scalability.     

Modelling heat,water and carbon fluxes in mown grassland under multi-objective and multi-criteria constraints

A Monte Carlo-based calibration and uncertainty assessment was performed for heat, water and carbon (C) fluxes, simulated by a soil-plant-atmosphere system model (CoupModel), in mown grassland. Impact of different multi-objective and multi-criteria constraints was investigated on model performance and parameter behaviour. Good agreements between hourly modelled and measurement data were obtained for latent and sensible heat fluxes (R² = 0.61, ME = 0.48 MJ m⁻² day⁻¹), soil water contents (R² = 0.68, ME = 0.34%) and carbon-dioxide flux (R² = 0.60, ME = −0.18 g C m⁻² day⁻¹). Multi-objective and multi-criteria constraints were efficient in parameter conditioning, reducing simulation uncertainty and identifying critical parameters. Enforcing multi-constraints separately on heat, water and C processes resulted in the highest model improvement for that specific process, including some improvement too for other processes. Imposing multi-constraints on all groups of variables, associated with heat, water and C fluxes together, resulted in general effective parameters conditioning and model improvement.