Dynamic Chemical Processes Research Articles

Denitrification, dehydration and ozone loss during the 2015/2016 Arctic winter

Abstract. The 2015/2016 Arctic winter was one of the coldest stratospheric winters in recent years. A stable vortex formed by early December and the early winter was exceptionally cold. Cold pool temperatures dropped below the nitric acid trihydrate (NAT) existence temperature of about 195 K, thus allowing polar stratospheric clouds (PSCs) to form. The low temperatures in the polar stratosphere persisted until early March, allowing chlorine activation and catalytic ozone destruction. Satellite observations indicate that sedimentation of PSC particles led to denitrification as well as dehydration of stratospheric layers. Model simulations of the 2015/2016 Arctic winter nudged toward European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data were performed with the atmospheric chemistry–climate model ECHAM5/MESSy Atmospheric Chemistry (EMAC) for the Polar Stratosphere in a Changing Climate (POLSTRACC) campaign. POLSTRACC is a High Altitude and Long Range Research Aircraft (HALO) mission aimed at the investigation of the structure, composition and evolution of the Arctic upper troposphere and lower stratosphere (UTLS). The chemical and physical processes involved in Arctic stratospheric ozone depletion, transport and mixing processes in the UTLS at high latitudes, PSCs and cirrus clouds are investigated. In this study, an overview of the chemistry and dynamics of the 2015/2016 Arctic winter as simulated with EMAC is given. Further, chemical–dynamical processes such as denitrification, dehydration and ozone loss during the 2015/2016 Arctic winter are investigated. Comparisons to satellite observations by the Aura Microwave Limb Sounder (Aura/MLS) as well as to airborne measurements with the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) performed aboard HALO during the POLSTRACC campaign show that the EMAC simulations nudged toward ECMWF analysis generally agree well with observations. We derive a maximum polar stratospheric O3 loss of ∼ 2 ppmv or 117 DU in terms of column ozone in mid-March. The stratosphere was denitrified by about 4–8 ppbv HNO3 and dehydrated by about 0.6–1 ppmv H2O from the middle to the end of February. While ozone loss was quite strong, but not as strong as in 2010/2011, denitrification and dehydration were so far the strongest observed in the Arctic stratosphere in at least the past 10 years.

Intrinsic and light-induced nonadiabatic phenomena in the NaI molecule

Nonadiabatic effects play a very important role in controlling chemical dynamical processes. They are strongly related to avoided crossings (AC) or conical intersections (CIs) which can either be present naturally or induced by classical laser light in a molecular system. The latter are named as "light-induced avoided crossings" (LIACs) and "light-induced conical intersections" (LICIs). By performing one or two dimensional quantum dynamical calculations LIAC and LICI situations can easily be created even in diatomic molecules. Applying such calculations for the NaI molecule, which is a strongly coupled diatomic in field free case, significant differences between the impact of the LIAC and LICI on the ground state population dynamics were observed. Moreover, obtained results undoubtedly demonstrate that the effect of the LIAC and LICI on the dynamics strongly depends on the intensity and the frequency of the applied laser field as well as the permanent dipole moments of the molecule.

Enhanced Temporal Resolution with Ion Channel-Functionalized Sensors Using a Conductance-Based Measurement Protocol.

The binding of a target analyte to an ion channel (IC), which is readily detected electrochemically in a label-free manner with single-molecule selectivity and specificity, has generated widespread interest in using natural and engineered ICs as transducers in biosensing platforms. To date, the majority of developments in IC-functionalized sensing have focused on IC selectivity or sensitivity or development of suitable membrane environments and aperture geometries. Comparatively little work has addressed analytical performance criteria, particularly criteria required for temporal measurements of dynamic processes. We report a measurement protocol suitable for rapid, time-resolved monitoring (≤30 ms) of IC-modulated membrane conductance. Key features of this protocol include the reduction of membrane area and the use of small voltage steps (10 mV) and short duration voltage pulses (10 ms), which have the net effect of reducing the capacitive charging and decreasing the time required to achieve steady state currents. Application of a conductance protocol employing three sequential, 10 ms voltage steps (-10 mV, -20 mV, -30 mV) in an alternating, pyramid-like arrangement enabled sampling of membrane conductance every 30 ms. Using this protocol, dynamic IC measurements on black lipid membranes (BLMs) functionalized with gramicidin A were conducted using a fast perfusion system. BLM conductance decreased by 76 ± 7.5% within 30 ms of switching from solutions containing 0 to 1 M Ca2+, which demonstrates the feasibility of using this approach to monitor rapid, dynamic chemical processes. Rapid conductance measurements will be broadly applicable to IC-based sensors that undergo analyte-specific gating.

Single-wavelength-controlled in situ dynamic super-resolution fluorescence imaging for block copolymer nanostructures via blue-light-switchable FRAP.

Photoswitchable fluorophores are promising in single-molecule optical devices and super-resolution fluorescence imaging, especially in single-molecule photo-activated localization microscopy (PALM) or stochastic optical reconstruction microscopy (STORM). However, the scarcity of current photoswitchable fluorophores stimulates researchers to develop complicated optical systems and processing software, in accordance with the limited photoswitchable fluorescent proteins and organic fluorophores. Previous efforts to develop synthetic photoswitchable fluorophores have exhibited their promising potential in super-resolution fluorescence imaging. Here, we have designed and synthesized a fluorescence molecular switch with reversible green emission, a napthalimide-hexaarylbiimidazole conjugate (NI-N-HABI), which exhibits strong fluorescence in the emissive state, with fast thermal fading of the photochromism and spontaneous fluorescence recovery after photobleaching (FRAP) induced by blue-light. The photoswitchable fluorophore enables the red-edge wavelength of the optical response to red-shift from the initial near-UV region at less than 400 nm, to 500 nm. The relatively fast fading speed of NI-N-HABI and its sensitivity to longer blue-light irradiation (400-500 nm) have allowed simplification of the optical microscopic system from a two-wavelength laser source to a single-wavelength laser. We applied NI-N-HABI in single-wavelength-controlled in situ dynamic super-resolution fluorescence imaging for the self-assembly and solvent annealing of amphiphilic block polymers, with 50 nm of optical resolution. Single-wavelength-controlled dynamic super-resolution fluorescence imaging facilitates nanoscale optical visualization for the dynamic physical and chemical fluctuation processes of stimuli-responsive nanostructures.

Manipulating and Visualizing Molecular Interactions in Customized Nanoscale Spaces.

We present a dynamically adjustable nanofluidic platform for formatting the conformations of and visualizing the interaction kinetics between biomolecules in solution, offering new time resolution and control of the reaction processes. This platform extends convex lens-induced confinement (CLiC), a technique for imaging molecules under confinement, by introducing a system for in situ modification of the chemical environment; this system uses a deep microchannel to diffusively exchange reagents within the nanoscale imaging region, whose height is fixed by a nanopost array. To illustrate, we visualize and manipulate salt-induced, surfactant-induced, and enzyme-induced reactions between small-molecule reagents and DNA molecules, where the conformations of the DNA molecules are formatted by the imposed nanoscale confinement. In response to dynamically modifying the local salt concentration, we report two salt-induced transitions in DNA molecules which occur on separate time scales: a rapid change in polymer extension due to modified local ionic screening and a gradual change in polymer brightness, reflecting release of intercalated YOYO-1 dye. Our time-resolved measurements provide new insights into the influence of YOYO-1 dye on polymer stiffness. In response to introducing cationic surfactants in solution, we temporally resolve single-molecule compaction trajectories of DNA polymers, guided by the confining nanogroove environment; this is in contrast to the uncontrolled collapse which would occur in free solution under similar conditions. In the presence of restriction enzymes, we directly visualize the cleavage of multiple DNA sites under adjustable nanoscale confinement. By using nanofabricated, nonabsorbing, low-background glass walls to confine biomolecules, our nanofluidic platform facilitates quantitative exploration of physiologically and biotechnologically relevant processes at the nanoscale. This device provides new kinetic information about dynamic chemical processes at the single-molecule level, using advancements in the CLiC design including a microchannel-based diffuser and postarray-based dialysis slit.

Ultrafast Nanocrystals Decorated Micromotors for On-Site Dynamic Chemical Processes.

CdS-polyaniline-Pt and ZnS-polyaniline-Pt micromotors have been synthesized and characterized. The nanocrystals are generated "in situ" during the template electrosynthesis of the micromotors while being simultaneously trapped in the polymeric network, generating a hybrid structure. The presence of nanocrystal "edges" in the inner polyaniline layer result in a rough Pt catalytic surface and enhanced electron transfer for highly efficient bubble propulsion at remarkable speeds of over 2500 μm/s. The incorporation of CdS and ZnS nanocrystals impart several attractive functions, including cation-exchange based chemical transformation capabilities and enhanced photocatalytic performance. The remarkable ion-exchange properties of ZnS-polyaniline (PANI)-Pt micromotors are illustrated for the cation exchange of heavy metals cations. The superior photocatalytic performance of CdS-PANI-Pt micromotors is used for the enhanced photocatalytic oxidation of bisphenol A. Such self-propelled micromotors act as highly efficient dynamic platforms that offer significantly shorter and more efficient processes as compared with common static operations. The attractive properties of these micromotors will pave the way for diverse sensing, decontamination, energy generation, or electronic applications.

Direct ab Initio (Meta-)Surface-Hopping Dynamics.

Tractable methods for studying the molecular dynamics of chemical processes driven by electronic nonadiabaticity are highly sought after to provide insight into, for example, photochemical reaction mechanisms, molecular collisions, and thermalized electronic band structures. Starting from the time-dependent Schrödinger equation for a many-body system, a direct ab initio trajectory surface-hopping (TSH) method relying on an analytical treatment of nonadiabatic couplings between electronic states is developed in this work. An approach that combines time-dependent perturbation theory and explicit time evolution via TSH to expedite calculation of nonadiabatic transition rates, namely, meta-surface-hopping dynamics, is presented, and an extrapolatory approach using time-dependent perturbation theory for recovering unbiased transition rates is assessed. The meta-surface-hopping method is applied to the problem of estimating nonradiative relaxation rates of a photoexcited iminium ion, CH₂NH₂⁺, and evidence for internal consistency of the combined dynamics/perturbation theory approach is presented.

Control of sulfide and methane production in anaerobic sewer systems by means of Downstream Nitrite Dosage

Bioproduction of hydrogen sulfide (H2S) and methane (CH4) under anaerobic conditions in sewer pipes causes detrimental effects on both sewer facilities and surrounding environment. Among the strategies used to mitigate the production of both compounds, the addition of nitrite (NO2−) has shown a greater long-term inhibitory effect compared with other oxidants such as nitrate or oxygen. The aim of this study was to determine the effectiveness of a new method, the Downstream Nitrite Dosage strategy (DNO2D), to control H2S and CH4 emissions in sewers. Treatment effectiveness was assessed on H2S and CH4 abatement on the effluent of a laboratory sewer pilot plant that mimics a full-scale anaerobic rising sewer. The experiment was divided in three different periods: system setup (period 1), nitrite addition (period 2) and system recovery (period 3). Different process and molecular methods were combined to investigate the impact of NO2− addition on H2S and CH4 production. Results showed that H2S load was reduced completely during nitrite addition when compared to period 1 due to H2S oxidation but increased immediately after nitrite addition stopped. The H2S overproduction during recovery period was associated with the bacterial reduction of different sulfur species (elemental sulfur/thiosulfate/sulfite) accumulated within the sewer biofilm matrix. Oxidation of CH4 was also detected during period 2 but, contrary to sulfide production, re-establishment of methanogenesis was not immediate after stopping nitrite dosing. The analysis of bulk and active microbial communities along experimental treatment showed compositional changes that agreed with the observed dynamics of chemical processes. Results of this study show that DNO2D strategy could significantly reduce H2S and CH4 emissions from sewers during the addition period but also suggest that microbial agents involved in such processes show a high resilience towards chemical stressors, thus favoring the re-establishment of H2S and CH4 production after stopping nitrite addition.

Graphical analysis of transient absorption spectra using the phasor approach

Transient absorption spectroscopy is a powerful tool to study chemical dynamic processes. Several methods have been developed for transient absorption spectra data analysis, such as the singular value decomposition with exponential fitting method. Here, we use a transient absorption phasor approach to transient absorption spectra data graphical analysis which is developed from the phasor approach. This expands the research processes of the phasor approach and makes the visual analysis of different kinetic processes possible. The lifetime can be evaluated in phasor space without professional exponential fitting. The method is computationally efficient and straightforward to implement. The simulation result validates the effectiveness of the presented method to transient absorption spectra data analysis. The transient absorption phasor approach has the potential to simplify transient absorption spectra data analysis and paves the way for the analysis of large data sets.

Least costly closed-loop performance diagnosis and plant re-identification

The inherent time-varying nature of dynamics in chemical processes often limits the lifetime performance of model-based control systems, as the plant and disturbance dynamics change over time. A critical step in the maintenance of model-based controllers is distinguishing control-relevant plant changes from variations in disturbance characteristics. In this paper, prediction error identification is used to evaluate a hypothesis test that detects if the performance drop arises from control-relevant plant changes. The decision rule is assessed by verifying whether an identified model of the true plant lies outside the set of all plant models that lead to adequate closed-loop performance. A unified experiment design framework is presented in the least costly context (i.e., least intrusion of nominal plant operation) to address the problem of input signal design for performance diagnosis and plant re-identification when the performance drop is due to plant changes. The application of the presented performance diagnosis approach to a (nonlinear) chemical reactor demonstrates the effectiveness of the approach in detecting the cause of an observed closed-loop performance drop based on the designed least costly diagnosis experiment.

Strain-Induced Reactivity in the Dynamic Covalent Chemistry of Macrocyclic Imines.

The displacement of molecular structures from their thermodynamically most stable state by imposition of various types of electronic and conformational constraints generates highly strained entities that tend to release the accumulated strain energy by undergoing either structural changes or chemical reactions. The latter case amounts to strain-induced reactivity (SIR) that may enforce specific chemical transformations. A particular case concerns dynamic covalent chemistry which may present SIR, whereby reversible reactions are activated by coupling to a high-energy state. We herewith describe such a dynamic covalent chemical (DCC) system involving the reversible imine formation reaction. It is based on the formation of strained macrocyclic bis-imine metal complexes in which the macrocyclic ligand is in a high energy form enforced by the coordination of the metal cation. Subsequent demetallation generates a highly strained free macrocycle that releases its accumulated strain energy by hydrolysis and reassembly into a resting state. Specifically, the metal-templated condensation of a dialdehyde with a linear diamine leads to a bis-imine [1+1]-macrocyclic complex in which the macrocyclic ligand is in a coordination-enforced strained conformation. Removal of the metal cation by a competing ligand yields a highly reactive [1+1]-macrocycle, which then undergoes hydrolysis to transient non-cyclic aminoaldehyde species, which then recondense to a strain-free [2+2]-macrocyclic resting state. The process can be monitored by (1) H NMR spectroscopy. Energy differences between different conformational states have been evaluated by Hartree-Fock (HF) computations. One may note that the stabilisation of high-energy molecular forms by metal ion coordination followed by removal of the latter, offers a general procedure for producing out-of-equilibrium molecular states, the fate of which may then be examined, in particular when coupled to dynamic covalent chemical processes.

Application of OpenModelica® in the mathematical modeling and simulation of general copper pipe corrosion

The application of mathematical modeling and simulation-based tools in chemical science helps to link scientific theories to real-time complex dynamic chemical processes. In this work, Modelica programming language is applied to model the general corrosion of copper pipes during stagnation of water in the pipes. The corrosion process was simulated in OpenModelica simulation environment. The simulation package is based on three general corrosion sub-processes: copper oxidation by dissolved oxygen present in water; precipitation of malachite on the pipe surface; dissolution of malachite from the pipe surface. These sub-processes also affect the physico-chemical quality of water, i.e., pH, alkalinity, ionic strength, chemical complex formation, etc. In the model setup, the chemical reactions describing the processes were first expressed as rate equations. The rate equations and other equations describing the system were then transferred to the OpenModelica software environment. The simulation package was validated by simulating two different laboratory corrosion experiments and comparing the simulation results with the results of the experiments. The developed simulation package effectively simulated generalized copper pipe corrosion during water stagnation in pipes.

Correntropy based data reconciliation and gross error detection and identification for nonlinear dynamic processes

Measurement information in dynamic chemical processes is subject to corruption. Although nonlinear dynamic data reconciliation (NDDR) utilizes enhanced simultaneous optimization and solution techniques associated with a finite calculation horizon, it is still affected by different types of gross errors. In this paper, two algorithms of data processing, including correntropy based NDDR (CNDDR) as well as gross error detection and identification (GEDI), are developed to improve the quality of the data measurements. CNDDR's reconciliation and estimation are accurate in spite of the presence of gross errors. In addition to CNDDR, GEDI with a hypothesis testing and a distance–time step criterion identifies types of gross errors in dynamic systems. Through a case study of the free radical polymerization of styrene in a complex nonlinear dynamic chemical process, CNDDR greatly decreases the influence of the gross errors on the reconciled results and GEDI successfully classifies the types of gross errors of the measured data.

Spatially resolved chemical reaction monitoring using magnetic resonance imaging.

Over the previous three decades, the use of MRI for studying dynamic physical and chemical processes of materials systems has grown significantly. This mini-review provides a brief introduction to relevant principles of MRI, including methods of spatial localization, factors contributing to image contrast, and chemical shift imaging. A few historical examples of (1) H MRI for reaction monitoring will be presented, followed by a review of recent research including (1) H MRI studies of gelation and biofilms, (1) H, (7) Li, and (11) B MRI studies of electrochemical systems, in vivo glucose metabolism monitored with (19) F MRI, and in situ temperature monitoring with (27) Al MRI. Copyright © 2015 John Wiley & Sons, Ltd.

Chemistry in motion: tiny synthetic motors.

CONSPECTUS: Diffusion is the principal transport mechanism that controls the motion of solute molecules and other species in solution; however, the random walk process that underlies diffusion is slow and often nonspecific. Although diffusion is an essential mechanism for transport in the biological realm, biological systems have devised more efficient transport mechanisms using molecular motors. Most biological motors utilize some form of chemical energy derived from their surroundings to induce conformational changes in order to carry out specific functions. These small molecular motors operate in the presence of strong thermal fluctuations and in the regime of low Reynolds numbers, where viscous forces dominate inertial forces. Thus, their dynamical behavior is fundamentally different from that of macroscopic motors, and different mechanisms are responsible for the production of useful mechanical motion. There is no reason why our interest should be confined to the small motors that occur naturally in biological systems. Recently, micron and nanoscale motors that use chemical energy to produce directed motion by a number of different mechanisms have been made in the laboratory. These small synthetic motors also experience strong thermal fluctuations and operate in regimes where viscous forces dominate. Potentially, these motors could be directed to perform different transport tasks, analogous to those of biological motors, for both in vivo and in vitro applications. Although some synthetic motors execute conformational changes to effect motion, the majority do not, and, instead, they use other mechanisms to convert chemical energy into directed motion. In this Account, we describe how synthetic motors that operate by self-diffusiophoresis make use of a self-generated concentration gradient to drive motor motion. A description of propulsion by self-diffusiophoresis is presented for Janus particle motors comprising catalytic and noncatalytic faces. The properties of the dynamics of chemically powered motors are illustrated by presenting the results of particle-based simulations of sphere-dimer motors constructed from linked catalytic and noncatalytic spheres. The geometries of both Janus and sphere-dimer motors with asymmetric catalytic activity support the formation of concentration gradients around the motors. Because directed motion can occur only when the system is not in equilibrium, the nature of the environment and the role it plays in motor dynamics are described. Rotational Brownian motion also acts to limit directed motion, and it has especially strong effects for very small motors. We address the following question: how small can motors be and still exhibit effects due to propulsion, even if only to enhance diffusion? Synthetic motors have the potential to transform the manner in which chemical dynamical processes are carried out for a wide range of applications.

How a plant simulator can improve industrial safety

Keeping the systems and processes safe is of paramount importance for all industries around the world. Process industry is a socio-complex system constituted of dynamic chemical processes, sophisticated computer algorithms, modern human machine interfaces, and teams of operators working at different locations. The decisions of the operators directly or indirectly influence the safety and production of chemical processes. The article presents and discusses a solution for immersive training of industrial operators that allows experiencing the multifaceted scenarios of (real) plant operations. This tool, called Plant Simulator (PS), combines a process simulator and an accident simulator to simulate dynamically both normal and abnormal/accident scenarios. These simulators are the engines that work behind the curtains of an Immersive Virtual Environment and make possible the realism of the simulated operations in the plant. The article explains the features of PS and discusses two case studies that show the potential improvements achievable in processes safety. © 2014 American Institute of Chemical Engineers Process Saf Prog 34: 237–243, 2015

Thinking on functional mechanism of acupuncture for inflammatory bowel diseases based on Metabolomics

Acupuncture has a good therapeutic effect in treatment of inflammatory bowel diseases (IBD), but its functional mechanism has not been systematically explained. Metabolomics is the scientific study of dynamic chemical processes involving metabolites as well as metabolic response of living organisms. Metabolomics, a research method with integrity and dynamics, corresponds to the overall regulatory effect of acupuncture and is in line with the overall concept of traditional Chinese medicine (TCM) and the concept of homeostasis. In the recent years, metabolomics has been extensively applied to the clinical and experimental study of IBD, and its potential applied value has been unanimously acknowledged by the researchers. In this article, the application status of metabolomics in acupuncture is summarized, and the research ideas to study the mechanism of acupuncture in the regulation and control of IBD by metabolomics are preliminarily explored.

Optimal experiment design for nonlinear dynamic (bio)chemical systems using sequential semidefinite programming

Optimal experiment design (OED) for parameter estimation in nonlinear dynamic (bio)chemical processes is studied in this work. To reduce the uncertainty in an experiment, a suitable measure of the Fisher information matrix or variance–covariance matrix has to be optimized. In this work, novel optimization algorithms based on sequential semidefinite programming (SDP) are proposed. The sequential SDP approach has specific advantages over sequential quadratic programming in the context of OED. First of all, it guarantees on a matrix level a decrease of the uncertainty in the parameter estimation procedure by introducing a linear matrix inequality. Second, it allows an easy formulation of E‐optimal designs in a direct optimal control optimization scheme. Finally, a third advantage of SDP is that problems involving the inverse of a matrix can be easily reformulated. The proposed techniques are illustrated in the design of experiments for a fed‐batch bioreactor and a microbial kinetics case study. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1728–1739, 2014

A pinch-valve interface for automated sampling and monitoring of dynamic processes by gas chromatography-mass spectrometry

Gas chromatography (GC) is frequently used in qualitative and quantitative analysis of volatile organic molecules. In its most common embodiment, samples are prepared in the laboratory, and injected into the capillary column using an autosampler. Analytes are separated, and detected by one of several available detection systems, including mass spectrometry (MS). However, this mode of operation is not convenient when monitoring dynamic chemical systems – for example, reaction mixtures. Here we present a facile approach for automated sampling, and subsequent introduction of samples to a GC apparatus in order to enable monitoring of dynamic chemical processes in real time. The proposed system incorporates two pinch valves, a peristaltic pump, a thermoshaker, and an electronic control unit (Raspberry Pi microcomputer) with several relays. The device facilitates dosing small volumes of liquid samples to the injection port of a commercial GC-MS apparatus. A program in C language controls the operation of the pump (on/off, direction of flow) and actuation of the pinch valves, and it initiates GC-MS runs. The system has been characterised with artificial samples, and successfully used in the monitoring of transesterification reactions catalysed by single microbeads containing immobilised lipase, as well as in the monitoring of the extraction of natural products from plant tissue samples. We believe that – following further improvements – this automated approach may be adapted for monitoring industrial processes and environmental analysis.

Modelling the Deferred Impact of Failures When Considering the Availability of Production Systems

When considering the availability of a production system, it is likely that some equipment failures will not immediately impact production; that is to say, their impact is ‘deferred’. However, should this type of failure not be remedied, it will, in time affect production. The impact of a failure could be deferred for a number of reasons, e.g. transient cooling effects, chemical process dynamics, or the use of buffer storage capacity within a system. A system's ability to ‘adsorb’ critical equipment failures can have a significant effect on production availability. Often, the deferred impact of a failure is modelled as a time based delay, defining a fixed period of time before the failure has an effect on system performance. This approach is commonly used to model the delayed impact of failures of equipment Items such as heaters, chemical injection pumps, etc. However, deferred impact can also be related to the volume of buffer storage available within a system—in this case, when considering the benefit of such storage, using a purely time based approach can be an oversimplification. This is particularly true when the flow rate through a system varies significantly over time, or during the repair process. GL Noble Denton has developed a method whereby the deferred impact of failures can be incorporated into Monte Carlo Reliability Availability and Maintainability (RAM) models using a volume-based approach, in addition to the previously used time-based approach. This has provided significant benefits when modelling failures that are not immediately critical due to storage (e.g. ponds for water handling) and typical examples will be given. In addition, GL Noble Denton has also considered how the deferred impact of equipment failures can be restored following a failure and this will also be discussed. The paper also includes a case study to illustrate how the methods have been applied.