Lealon L. Martin

Potential of Eichhornia crassipes for biomass refining

Here we explore the utilization of Eichhornia crassipes, commonly known as water hyacinth, as a competitive source of biomass for conversion to fuel. Ecologically, E. crassipes is the most undesirable of a class of noxious and invasive aquatic vegetation. Water hyacinth grows rapidly on the surface of waterways, forming a dense mat which depletes the surrounding environment of essential nutrients. These properties, rarely encountered in other plant systems, are features of an ideal feedstock for renewable biomass. The high characteristic water content limits the range over which the material can be transported; however it also makes E. crassipes a natural substrate for rapid microbial metabolism that can be employed as a potentially effective biological pretreatment technology. We show through a life cycle analysis that water hyacinth is a competitive feedstock with the potential to be produced at a cost of approximately

Globally optimal power cycle synthesis via the Infinite-DimEnsionAl State-space (IDEAS) approach featuring minimum area with fixed utility

40 per ton of dry mass.

On the dynamic modeling of mammalian cell metabolism and mAb production

This paper demonstrates the use of the In%nite DimEnsionAl State space (IDEAS) approach in synthesizing optimal power cycles featuring minimum heat exchange area. IDEAS is used to synthesize power cycle networks which include splitters, mixers, pumps, turbines, and heat exchangers and feature a single or multiple working 8uid(s). The overall synthesis goal is to minimize heat exchange area requirements, while delivering a %xed percentage of the maximum net power obtainable from a given set of hot and cold utilities. The global optimality of the obtained power cycle network con%guration is guaranteed, since IDEAS gives rise to convex (linear) programs. The power of the proposed approach is demonstrated on a case study involving the generation of electricity by a bottoming cycle with a pure ammonia working 8uid. Real thermodynamic data for pure ammonia and rigorous equipment models are employed in carrying out the proposed optimization. ? 2002 Elsevier Ltd. All rights reserved.

Total annualized cost optimality properties of state space models for mass and heat exchanger networks

Abstract A general optimization-based technique for the estimation of kinetic parameter values in dynamic models of cell metabolism is presented. A discretization strategy is used to transform continuous differential equations given in the model into an approximating set of algebraic equations. The discretized equation set is then used to constrain a non-linear optimization problem, whose solution is an optimal set of model parameter values. As a case study, we examine a simplified dynamic model of mammalian cell culture [Gao, J., Gorenflo, V. M., Scharer, J. M., & Budman, H. M. (2007). Dynamic metabolic modeling for a mab bioprocess. Biotechnology Progress, 23 (1), 168–181]. Our parameter estimation technique is shown to solve the unsimplified variant of this model, and to provide a more accurate simulation of the experimentally observed system behavior than originally reported. We are additionally able to predict physically reasonable system data even in the absence of corresponding experimental measurements, and, finally, to provide a quantitative basis for challenging certain underlying assumptions in the original model solution.

A flexible state-space approach for the modeling of metabolic networks I: development of mathematical methods.

In this work, we employ a state space representation of a heat/mass exchanger network to derive a mathematical formulation of the minimum total annualized cost (TAC) problem. Mathematical properties of the resulting nonlinear programs global optimum are then derived, using a variation induced minimization (VIM) technique and control theoretic concepts. This technique successfully identifies variables which are zero at the global optimum, thus reducing the size of the optimization problem. It is established that, under certain conditions, all self-recycle and total network bypass flow rates can be chosen to be zero at the TAC minimum. Two heat exchange network (HEN) TAC synthesis problems are employed to illustrate the validity of these properties, as well as the importance of the conditions under which the properties are derived. A hybrid algorithm, which consists of branch and bound underestimation with imbedded interval analysis, is employed in identifying numerically the optimum of these HEN TAC problems.

A flexible state-space approach for the modeling of metabolic networks II: advanced interrogation of hybridoma metabolism.

We introduce a novel, flexible, optimization-based mathematical framework for the modeling of arbitrarily complex metabolic networks: topological metabolic analysis (TMA). The framework is adapted from state-space approaches used by Manousiouthakis and co-workers for the representation of complex heat- and mass-exchanger networks. We offer a thorough discussion of the mathematics and general theory underlying the framework, and discuss certain mathematical advantages of our modeling representation in comparison with other commonly used techniques (MFA and FBA). We employ a novel aggregate objective function for use with our basic constraint model, including a generalized least-squares term (for fitting available experimental measurements) and a linear design term (for representing biological or engineering goals). Using a case-study taken from recent literature (McKinlay et al., 2007), we demonstrate (among other benefits) the ability of this objective to identify alternate distinct-yet-equally optimal solutions for a given modeling problem. We also show that these solutions, obtained using only external metabolite uptake and secretion measurements, provide useful biological insights and compare favorably with solutions obtained on the basis of (13)C isotope-tracing data.

A minimum area (MA) targeting scheme for single component MEN and HEN synthesis

Having previously introduced the mathematical framework of topological metabolic analysis (TMA) - a novel optimization-based technique for modeling metabolic networks of arbitrary size and complexity - we demonstrate how TMA facilitates unique methods of metabolic interrogation. With the aid of several hybridoma metabolic investigations as case-studies (Bonarius et al., 1995, 1996, 2001), we first establish that the TMA framework identifies biologically important aspects of the metabolic network under investigation. We also show that the use of a structured weighting approach within our objective provides a substantial modeling benefit over an unstructured, uniform, weighting approach. We then illustrate the strength of TAM as an advanced interrogation technique, first by using TMA to prove the existence of (and to quantitatively describe) multiple topologically distinct configurations of a metabolic network that each optimally model a given set of experimental observations. We further show that such alternate topologies are indistinguishable using existing stoichiometric modeling techniques, and we explain the biological significance of the topological variables appearing within our model. By leveraging the manner in which TMA implements metabolite inputs and outputs, we also show that metabolites whose possible metabolic fates are inadequately described by a given network reconstruction can be quickly identified. Lastly, we show how the use of the TMA aggregate objective function (AOF) permits the identification of modeling solutions that can simultaneously consider experimental observations, underlying biological motivations, or even purely engineering- or design-based goals.

Targeting Maximum Reaction Conversion at Minimum Total Annualized Cost for a Spouted Fluidized Bed with a Draft Tube

Abstract A systematic methodology is developed that quantifies the minimum area (MA) target over all mass exchange/heat exchange networks with single component target compositions/temperatures. The resulting mathematical formulation is a Zero–One Integer Linear Program which is polynomially solvable. The methodology is illustrated through synthesis examples in which we identify MA targets for both heat exchange networks (HEN) and single component mass exchange networks (MEN). We further establish, through a rigorous mathematical proof, that co-current mass (heat) exchange configurations are sub-optimal to counter-current configurations in regard to a MA objective.

A nonlinear nonconvex minimum total heat transfer area formulation for ocean thermal energy conversion (OTEC) systems

The spouted fluidized bed with a draft tube (SFBDT) has been extensively studied and has a number of applications. However, future attention and studies are expected to focus on applications which involve reacting systems. In this work, we present the modeling equations for a SFBDT that describes and characterizes its behavior. These modeling equations, combined with the reaction kinetics and mass balance equations, provide an accurate mathematical description of the phenomenon. Here, we consider contact between a reactant solid-phase, consisting of uniformly sized particles (beads), with an annular reactant liquid phase side stream flowing through the bed. The hydrodynamic patterns between reactant fluid and beads are modeled as back-mixing flow. In addition, we assume the reactions are . A is the bead carrying unreacted chemical. B is the bead carrying desired product. C is the bead carrying product which loses its function. Models characterizing the reactions are presented and combined with modeling equations of SFBDT. Here we present an optimized SFBDT system where we achieve the maximum product concentration for a given set of reactants at the lowest cost. 1 2 k k A B C