dataesr/scientific-paragraphs-categorization huggingface dataset:
Comparison of Pump Performance Curves. The comparison of the delivery head curves obtained from numerical calculations and from the experiments for all five operational conditions of nominal speed is shown in Figure  10. For the CFD results, the delivery head was obtained from one averaged revolution of the unsteady calculation. Data from static pressure sensors were used in the experimental head calculation. Pump head was calculated based on the following equation: With regard to pump efficiency, the total efficiency is the product of hydraulic efficiency, mechanical efficiency, and volumetric efficiency, given by  (10). Only the hydraulic loss was considered in the numerical simulation; thus, the total efficiency should be calculated by (  6 ) to  (10). All of these equations are presented in the literature  [19] : 𝐻 = 1 𝜌𝑔 ( 𝑃 tot 󵄨 󵄨 󵄨 󵄨outlet -𝑃 tot 󵄨 󵄨 󵄨 󵄨inlet ) + 1 2𝑔 (V 2 out -V 2 in ) + (𝑧 out -𝑧 in ).
Acknowledgments This study was financially supported by the  State Key Program of National Natural Science of China  (Grant no. 51239005 ), the  National Natural Science Foundation of China  (Grant no. 51349004 ), and the  National Science & Technology Pillar Program  (Grant no. 2011BAF14B04 ) of China and sponsored by the  Research and Innovation Project for College Graduates of Jiangsu Province  ( CXZZ12 0679 ).
Results from simulated interferograms We begin our validation tests with five different simulated interferograms with 512 × 512 pixels size representing respectively a cone, a pyramid, a Gaussian variation and two phase images generated using meshgrid function in MATLAB as shown in Fig. 2. First, we filtered the simulated interferograms affected by a white Gaussian noise with σ 2 = 0. 8. Fpr , we assume that the error rate between the estimated phase φ and the observed one ϕ for one pixel should not exceed π 1000. So for the whole phase image with size N × N the global error rate will be compute as the sum of local error rate = N 2 π 1000 ( 10 ) note that more details about the relationship between the noise variance and the estimaton error threshold is given in  (Hongxing et al. , 2013). For the filtering results, we notice that the proposed approach reduce noise inside fringes very well.
Experimental data The data used to drive the revised GDM model were obtained from Machinet et al. [13]. Briefly fine roots (diameter 2-3 mm) of four natural genotypes of maize (F2, F2bm1, F292 and F292bm3), which differed in their chemical composition (Table  1 ), were cut into 5 mm lengths, added to soil in laboratory microcosms and incubated at 15uC. Potassium-nitrate fertilizer was added to microcosms to insure no nitrogen limitation  [17]. They monitored CO 2 -C efflux on days 3, 7, 10, 14, 21, 29, 36, 42, 51, 57, 70, 80, 87, 95 and 112. Chemical characteristics of litter were determined on days 0 (initial), 14, 36, 57 and 112, on roots manually removed from soils. Machinet et al. [11]  used the same experimental methods for 12 additional maize genotypes, but examined only the initial litter chemistry and measured CO 2 efflux during decomposition.
The suite of litter chemical characteristics reported by Machinet et al. [11, 13]  in root residues included C and N content, Van Soest soluble C (C-SOL) and N (N-SOL) contents, and cell wall polysaccharides: glucan (Glu), arabinan (Ara) and xylan (Xyl), which are the major polymer carbohydrates in graminaea, as well as galactan (Gal) and uronic acids contents (galacturonic (Ac Gal) and glucuronic (Ac Glu)). They also determined Klason lignin (KL) and the lignin monomers, guaiacyl (G) and syringyl (S), as well as ester-linked p-coumaric (pCA) and ferulic acids (FA ester ), and ether-linked ferulic acids (FA ether ). From these data we calculated the sum of cell wall sugars (gSug), arabinan:xylan ratio (A:X), carbon:nitrogen ratio (C:N), lignocellulose index (LCI = C 3 /[C 2 +C 3 ])) with C 1 ( = C-SOL), C 2 ( = gSug) and C 3 ( = KL), and non-detergent fiber (NDF) content.
Model revisions This model was programmed in MATLAB (The MathWorks Inc. , Natick, USA). We revised GDM to use Reverse Michaelis-Menten (RMM) functions to calculate decay rates as functions of microbial activity  [18] : dC i /dt = k i ?C i ?B j /(K Bji +B j ), where C i is the amount of substrate i, B j is the amount of microbial biomass in guild j, and K Bji is the half-saturation coefficient of guild j for substrate i. Note that we altered the more common RMM approach by using biomass (B) in place of an enzyme (E) pool, which assumes a constant ratio of E:B resulting from constitutive enzyme production  [16, 18]. We limited access to substrate pools by guilds: guild 1 was assumed to access only soluble resources (C 1 ); guild 2 was assumed to access both C 1 and C 2 ; guild 3 could access C 1 , C 2 and C 3 (Figure  1 ).
Optimizing parameter values The values of two key model parameters that showed correlations with initial chemistry, LCI T , and K B22 , were optimized for the four maize genotypes  [13]  using the fmincon function of the MATLAB Optimization Toolbox (The Math-Works, Inc. , Natick, USA), which applies a sequential quadratic programming algorithm. The objective function was the sum of the root mean square errors calculated between the experimental and simulated CO 2 efflux rates, cumulative amount of carbon mineralized over 112-days and chemical evolution in the C 1 and C 2 pools during decomposition, normalized by the means of the observations. We determined the best-fit estimates of parameters K B22 and LCI T that most closely matched simulations to observed patterns of CO 2 efflux and both C 1 and C 2 pools over time (Table  1 ).
Code descriptions The diversity of process models (Section 3) and numerical approaches (Section 4) used in the simulation of reactive transport in subsurface environments makes it nearly impossible for any code to include all potential capabilities or to run on all computer architectures, from workstations to distributed memory parallel systems. Further, code development has typically occurred incrementally over several years, in some cases over a decade or more, driven by the needs of research projects. The reactive transport codes used for this benchmarking effort reflect the heterogeneity resulting from this process; even when re-engineered from the ground up, the codes are the legacy of years of development and research. In some instances, development of native geochemical capabilities from scratch has been circumvented by coupling flow and transport codes, typically using an operator splitting approach, to existing geochemical capabilities.
In the code overview that follows, we start with PHREEQC, a geochemical code that is used as geochemical engine in HPx, PHT3D, and OpenGeoSys. HYTEC uses the same concept to bring in the geochemical capabilities of CHESS. We follow with codes that have native geochemical modules. ORCHESTRA is distinctive in that all model definitions are separate from the calculation engine or equation solver. TOUGHREACT and eSTOMP use the operator splitting approach, while HYDROGEOCHEM, CrunchFlow, MIN3P, and PFLOTRAN allow for implicit coupling of transport and biogeochemistry. Heterogeneous equilibria that can be imposed include surface complexation, ion exchange, fixed-composition gases and minerals, solid solutions, and a multicomponent gas phase. Surface complexation can be calculated by using the diffuse-double layer model or the CD-MUSIC model.
In addition, it is possible to calculate explicitly the composition of the diffuse layer that balances the charge accumulated by surface complexation. Solid solutions may be ideal-multicomponent or nonideal-binary solid solutions. The pitzer. dat and phreeqc. dat databases have additional features. Density and specific conductance are calculated as functions of the solution composition. Molar volumes of aqueous species are calculated as functions of pressure, temperature, and ionic strength, which allow calculation of the pressure dependence of equilibrium constants  [62]. These databases use the Peng-Robinson formulation for nonideal gas fugacities and can provide accurate simulations of mineral and gas solubilities up to 200 °C and 1,000 bar for major elements  [62]. It may be noted that the calculation of density-driven flow requires composition, temperature, and pressure-dependent solution densities such as calculated by PHREEQC.
The iso. dat database implements an approach to isotopes where each isotope is considered to be a separate thermodynamic component  [63]. The database allows simulation of kinetic and equilibrium fractionation of isotopes of carbon, hydrogen, nitrogen, oxygen, and sulfur and can be extended to other isotopes. Homogeneous or heterogeneous kinetic reactions can be defined with arbitrary rate expressions that are functions of solution composition and availability of solid reactants by using Basic programs that are evaluated with an embedded Basic interpreter. The general kinetic reaction capability of PHREEQC can be used for any biological reactions. It is possible to formulate any rate expression, including Monod or kinetics of any order, inhibition factors, rates that depend on free energy, and rate variation as a function of available electron acceptors.
Colloids, which can react as surface-complexation units, can be transported, coagulated, and resuspended depending on system properties and solute composition. Diffusion of interlayer (exchangeable) cations and of solutes in the diffuse layer of surfaces can be simulated. Dimensions 1D 1,2,3D 1,2,3D 1,2,3D 1,2,3D 1D 1,2,3D 1,2,3D 1,2,3D 1,2,3D 1,2,3D 1 Nearly any set of geochemical parameters and physical properties can be output to tab-delimited files or graphed with a built-in plotting capability that can produce multiple real-time plots simultaneously. Input for PHREEQC can be defined and run with a specialized module for Notepad++, or with one of two graphical user interfaces (PhreeqcI and Phreeqc for Windows; the latter uses PHREEQC version 2. 18). The wide range of geochemical capabilities offered by PHREEQC, its open-source code, as well as continued support and development by the U.
S. Geological Survey have made it attractive for many researchers to couple it as a geochemical module to existing flow and transport codes that exceed PHREEQC's native transport capabilities. Specifically for this purpose, PHREEQC has been encapsulated in the module IPhreeqc  [64]  to allow all PHREEQC functions to be called from C, C++, Fortran, or from scripting languages (IPhreeqcCOM), such as Excel macros, Python, or Matlab. Coupling is performed with a sequential noniterative approach (SNIA), i. e. , the same method as used in PHREEQC to couple transport and reactions. Some of these couplings are used to simulate unsaturated zone processes such as HPx  [65, 66] , saturated zone environments such as PHAST [64, 67] and PHT3D  [68] , and many more that are beyond the scope of this overview.
HPx (HP1, HP2, HP3) HPx, an acronym for HYDRUS  [69]  and PHREEQC  [60] , is a versatile coupled reactive transport code for variably saturated flow conditions. Originally released as a onedimensional flow and transport model about a decade ago  [70, 71] , it is now also available for multidimensional flow and transport problems  [65, 66]. Additionally, HPx codes are fully integrated in the well-designed graphical user interfaces of the HYDRUS codes  [51]. Combining the capabilities of the individual HYDRUS and PHREEQC codes, HPx can be used to simulate many different processes in variably saturated porous media: (1) transient water flow, (2) transport of multiple aqueous and gaseous components, (3) heat transport, and (4) a broad range of low-temperature biogeochemical reactions, including interactions of the liquid phase with minerals, gases, exchangers, and sorption surfaces, described using thermodynamic equilibrium, kinetic, or mixed equilibrium-kinetic formulations.
PHT3D PHT3D is a three-dimensional multicomponent reactive transport code specifically designed for simulating flow and reactive transport processes in saturated porous media. PHT3D couples the multispecies transport simulator MT3DMS  [83]  with the geochemical reaction model PHREEQC-2  [60]  via sequential operator-splitting. The coupling to MT3DMS provides several options of solution techniques for transport: (1) method of characteristics (MOC), (2) modified method of characteristics (MMOC), (3) hybrid method of characteristics (HMOC), (4) upstream finite difference method, and (5) thirdorder TVD scheme  [84]. The solution technique should be selected by the user based on the nature of the system being modeled (such as presence of sharp concentration gradients, redox reactions) and the selected discretization.
Through the flexible, generic nature of PHREEQC-2, PHT3D can handle a broad range of equilibrium and kinetic reactive processes, including aqueous complexation, mineral precipitation/dissolution, multisite cation exchange, and surface complexation reactions. The PHT3D code also has the capability to simulate kinetically reacting immobile components. Typical reactive processes such as microbial activity, NAPL dissolution, and isotopic fractionation can also be simulated. The structure of PHT3D code is such that these and other processes can be included through a PHREEQC-2 database files without modification of the PHT3D source code. PHT3D was developed in the 1990s and has been applied to diverse groundwater problems. In the original version, transport was calculated during a time step, an input file was written for PHREEQC for geochemical calculations, and these steps were repeated for subsequent time steps until finished  [85].
A second version was released in 2010 that tightened this reaction-transport coupling in the code to reduce computation time. In this version, PHREEQC is used for storing the chemical data of the model, including the chemical activities and the composition of surface complexes from the previous time step. A review of the developments in PHT3D version 2 and its potential applications were summarized by Appelo and Rolle  [86]. Previous modeling studies using PHT3D targeted natural and enhanced remediation of organic (e. g. , BTEX, CHCs) and inorganic (e. g. , metals) contaminants and the geochemical changes occurring during their degradation. Applications of PHT3D also included modeling the fate and transport of pesticides, reactive transport of arsenic and uranium, trace metal remediation by in situ reactive zones, temperature-dependent pyrite oxidation, and isotopic fractionation during natural attenuation of organic pollutants  [84].
Recently, PHT3D has been used to model interactions of seasonal aquifer thermal energy storage and groundwater contamination plumes  [87]  and radially symmetric flow and solute transport around point sources and sinks  [88]. Recent enhancements of the code include implementation of electrokinetic transport to deliver a remediation compound within heterogeneous and low-permeability sediments for in situ chemical oxidation  [89]. Further information regarding installation, user documentation, and benchmark test problems can be found at http://www. pht3d. org/. PHT3D has been integrated into the PMWIN preor postprocessing package so as to enhance its graphical user interface (GUI) and visualization capabilities. This PMWIN coupling provides users the flexibility to select from existing reaction packages/database files or develop and integrate newly developed packages  [90].
OpenGeoSys OpenGeoSys (OGS) is a scientific open-source initiative for numerical simulation of thermo-hydromechanical/chemical processes in porous and fractured media. The basic concept is to provide a flexible numerical framework for solving coupled multifield problems. The OGS code is targeting primarily applications in environmental geoscience, e. g. , in the fields of contaminant hydrology, water resources management, waste deposits, or geothermal systems, but it has also been applied to new topics in energy storage  [91]. The software is written with an object-oriented finite element method concept, including a broad spectrum of interfaces for pre-and postprocessing  [92]. The OGS developer environment provides an open platform that includes professional software-engineering tools such as platformindependent compiling and automated result testing tools.
To ensure the quality of the code and facilitate communications among different developers, more than 150 benchmarks are recently validated before any changes in the source code are released. In addition, the OGS community has been active in several international benchmarking initiatives, including e. g. DEVOVALEX (with applications mainly in waste repositories, Rutqvist  [93] , CO2BENCH and Sim-SEQ (in CO 2 sequestration,  [94, 95] ). The book containing over 100 wellverified benchmarks has been published recently  [96]. In OGS, heterogeneous or porous-fractured media can be handled by dual continua or discrete approaches, i. e. , by coupling elements of different dimensions. OGS has a built-in random-walk particle tracking method for Euler-Lagrange simulations  [97]  and can simulate incompressible and compressible flow  [98] , densitydependent flow  [99] , unsaturated flow  [100] , two-phase flow  [101, 102] , and overland flow  [103].
All flow model components are available for non-isothermal conditions and for deformable porous media. Equations of state (EoS) for several fluids (gases, supercritical fluids) are available to module temperature-driven dynamics  [104]. Multicomponent mass transport and (equilibrium and nonequilibrium) heat transport  [105]  modules are part of OGS. The OGS Tool-Box  [106]  promotes functionality extension through code coupling interfaces for example coupling external geochemical and biogeochemical simulation tools such as PHREEQC/IPhreeqc, GEMS, and BRNS, in addition to the underlying internal process couplings. This flexibility has made it possible for OGS to simulate geochemical processes such as ion exchange, mineral dissolution/precipitation, and equilibrium reactions in partly saturated bentonites (OGS#PHREEQC-2  [107] ), formation of solid solutions and radionuclide retardation (OGS#GEMS  [108] ), and thermochemistry for technical energy storage  [91] , as well as microbiological reactions such as Michaelis-Menten degradation kinetics to estimating in situ degradation rates  [109]  and organic carbon degradation via multiple microbial degradation pathways, dispersive mixing controlled bio-reactive transport with different reaction kinetics (OGS#BRNS  [110] ).
The OpenGeoSys community has been in development since the mid-1980s and the numerical simulator has been continuously re-engineered through Fortran, C, and C++ implementations and in the meantime the code has been optimized for massively parallel machines, e. g. , JUQUEEN. The OGS community also developed continuous workflows that include various interfaces for pre-and postprocessing. Additionally, visual data integration became an important tool for establishing and validating data driven models  [111]  since three-dimensional visualization facilities, such as the UFZ-VISLAB (Leipzig, Germany), can be used for comprehensive systems analysis, computational steering, and demonstration purposes for stakeholder and authorities. Detailed information regarding code, benchmarks, and community is available through: opengeosys.
Thermodynamic data are taken from international databases, e. g. , EQ 3/6  [113]. The hydrodynamic module of HYTEC is adapted for hydrodynamic conditions commonly encountered in the laboratory or in the field. The code allows for dual porosity, saturated, unsaturated or two-phase flow, variable boundary conditions, sinks, and sources  [114]. HYTEC searches for an accurate solution to the multicomponent transport problem using an iterative, sequential, so-called strong coupling scheme. Strong coupling permits variable hydrodynamic parameters as a function of the local chemistry  [115]. For example, the porosity of a porous medium decreases after massive precipitation of newly formed mineral phases, which modifies the water flow paths and transport parameters, e. g. , diffusion coefficients.
ORCHESTRA ORCHESTRA is a platform developed by Meeussen  [126]  for modeling equilibrium chemistry, with the option of including kinetics and/or transport processes. ORCHES-TRA does not enforce a specific model, but is rather a generic toolbox that allows users to create their own models using an object representation, which is stored in an object database and is fully user-definable. In ORCHESTRA, reactive transport processes are implemented by a mixing-cell concept. This implies that transport systems can be composed of (well-mixed) cells and connections between these cells. The cells contain the information on the local physical and chemical composition, while the connections between the cells contain the mass transport equations (diffusion, convection, etc. ). Both the connections between the cells, but also the literal equations involved in mass transport, are defined in text input files.
Thus, ORCHESTRA provides the flexibility to the users to adapt the model structure and equations. Effectively, the mixing-cell concept results in a finite difference scheme. In ORCHESTRA, it is possible to choose a sequential iteration (SIA) approach (predictor corrector method) or a non-iterative approach (SNIA) solved with a fourth order Runge-Kutta method. With SNIA, the kinetic reactions are solved using the same time step as the transport processes. ORCHESTRA is coded in Java, which results in an executable code that runs on different operating systems (e. g. , Windows, Linux, Unix, Solaris, OSX). Java also contains standard language constructs for parallel programming, which facilitates parallelization and makes efficient use of multiprocessor hardware. In contrast with the IPhreeqc method for parallelization that uses domain decomposition with nodes/cells predefined for each processor, the ORCHESTRA approach uses a single node pool, from which nodes are taken by each available processor.
Since 2010, code development has continued at the Nuclear Research and Consultancy Group. Recent applications of the model include coupling of ORCHESTRA with LeachXS database to improve understanding and prediction of the long-term performance of cementitious barriers used in nuclear applications. This thermo-hydro-mechanical (THM) coupling has also been used to assess long-term release behavior of sulfidic mining wastes  [134] , carbonation-induced corrosion in highlevel waste tanks  [135] , and uncertainty quantification of thermodynamic parameters  [136]. More information on code development and example applications is available at http://www. macaulay. ac. uk/ORCHESTRA/.
An operator splitting solution method is used for flow, transport, and reactions, each of which employs implicit time-stepping schemes. The resulting equations are nonlinear coupled algebraic equations, which are solved using Newton-Raphson iteration. Flow and solute transport are solved using parallel iterative conjugate gradient techniques as implemented in the Portable Extensible Toolkit for Scientific Computation (PETSc) libraries  [162]. Differential algebraic equation solver techniques are used for the standard biogeochemical reaction network and the IBM ILOG CPLEX optimization solver package is used for the constraint-based system of metabolic pathway reactions. Input is directed through semi-formatted text files and output is available through a variety of user-directed formats. The simulator recognizes a number of boundary condition types and allows their specification both internally and externally to the computational domain.